Wind Parks and Hydro Pumping Plants Coordinated Operation · The hydro power plants equipped with...

Setembro de 2010

Wind Parks and Hydro Pumping Plants Coordinated

Operation

Pedro Miguel Pereira Mendes

Dissertação para obtenção do Grau de Mestre em

Engenharia Electrotécnica e de Computadores

Júri

Presidente: Prof. Paulo José da Costa Branco Orientador: Prof. Rui Manuel Gameiro de Castro Co-Orientador: Prof. José Manuel Dias Ferreira de Jesus Vogal: Prof. Pedro Manuel Santos de Carvalho

i

Agradecimentos

Ao Professor Rui Castro, pela confiança depositada em mim, pela disponibilidade sempre

demonstrada e pela formação e acompanhamento que sempre me deu na minha passagem pelo

Instituto Superior Técnico.

Ao Professor Ferreira de Jesus, pela total disponibilidade, interesse e empenho demonstrados

para o esclarecimento das muitas dúvidas que lhe coloquei durante esta tese e este curso.

À minha família, em especial aos meus pais pelo enorme esforço que fazem diariamente para

que eu possa terminar a minha formação académica e por toda a formação como pessoa que me

deram.

À minha namorada, por toda a amizade e suporte que me deu e, essencialmente, pela

estabilidade que me proporcionou nos últimos sete anos, que foi essencial para o meu sucesso.

Aos meus amigos. Aos muitos que já tinha antes de ingressar nesta universidade e àqueles que

aqui fiz, que sempre me apoiaram e tiveram sempre grande confiança em mim. A estes últimos, um

especial obrigado pelo grande companheirismo e pelo bom ambiente que sempre souberam

proporcionar para que fosse mais fácil para todos a conclusão deste difícil curso.

A todos, obrigado.

ii

Resumo

A produção de energia eólica depende da velocidade do vento, a qual apresenta variações de

longo e curto prazo. Enquanto as primeiras seguem aproximadamente padrões sazonais, as

segundas são dificilmente previsíveis e, por este motivo, a integração em larga escala de parques

eólicos no sistema eléctrico pode ter implicações na sua segurança e estabilidade.

Devido à capacidade de variar rapidamente o seu ponto de operação, as centrais hídricas

surgem como a solução mais viável para promover a integração da produção eólica, pois são

capazes de compensar as variações de curto prazo da produção eólica, mantendo o equilíbrio entre a

geração e a demanda. As centrais hídricas equipadas com bombagem, além da sua flexibilidade de

operação, permitem ainda armazenar o excedente de produção eólica sob a forma de água,

bombeando-a para os seus reservatórios a montante.

Neste trabalho desenvolveu-se um algoritmo que permite estudar a viabilidade técnica da

coordenação de duas centrais hídricas com bombagem com toda a potência eólica instalada em

Portugal, de forma a manter a potência de saída deste agregado num valor alvo constante durante

todo o ano. Registos históricos de 2007 de produção e carga, vistos de vários pontos da rede de

transporte, servem de base às simulações realizadas.

Os resultados obtidos evidenciam que o fornecimento contínuo da potência alvo, durante todo o

ano, depende bastante do próprio valor alvo estabelecido, dos valores das potências instaladas de

cada uma das tecnologias (eólica e hídrica) bem como da capacidade de armazenamento de ambos

os reservatórios das centrais hídricas.

Palavras-chave: energia eólica, central hídrica com bombagem, operação coordenada,

armazenamento de energia, potência alvo.

iii

Abstract

The wind power production depends on wind speed, which experiences long and short term

variations. While the first follow roughly seasonal patterns, the latter are difficult to predict and,

therefore, the large-scale integration of wind parks in the electric system may have implications for its

security and stability.

Due to their ability to quickly vary their operation point, hydro power plants emerge as the most

viable solution to promote the integration of wind power production, as they are able to compensate

the short term variations of wind production, maintaining the balance between global generation and

demand. The hydro power plants equipped with pumping systems allow, in addition to the flexible

operation, storing the excess of wind power in the form of water, pumping it to their superior

reservoirs.

This work comprises the development of an algorithm that allows studying the technical feasibility

of coordinating two hydro pumping plants with all the wind power installed capacity in Portugal, in

order to maintain the power output of this aggregate constant at a target value, throughout the year.

Historical records of the power production and demand seen from different points of the transmission

grid are the background for the simulations.

The results obtained show that the continuous supply of the target power throughout the year

depend largely on the established target value itself, on the values of the installed capacity of each

technology (wind and hydro), as well as on the storage capacity of both reservoirs of the hydro

pumping plants.

Keywords: wind power, hydro pumping plant, coordinated operation, energy storage, target

power.

iv

Table of Contents

List of Figures................................................................................................................... vii

List of Tables ................................................................................................................... viii

Abbreviations ................................................................................................................... ix

1. Introduction ............................................................................................................... 1

1.1. Historical Background .................................................................................................... 1

1.2. Renewable Energy Sources – General Overview ............................................................. 3

1.3. Motivations and Objectives ........................................................................................... 5

1.4. Structure of the Thesis ................................................................................................... 6

2. Wind Power ............................................................................................................... 7

2.1. General Situation ........................................................................................................... 7

2.1.1. Context and Background............................................................................................................... 7

2.1.1.1. Worldwide ................................................................................................................................ 7

2.1.1.2. In Portugal ................................................................................................................................ 9

2.1.2. Future Prospects ......................................................................................................................... 10

2.1.2.1. Offshore Wind Turbines ......................................................................................................... 11

2.2. The Wind Resource ...................................................................................................... 12

2.2.1. Wind Characteristics ................................................................................................................... 12

2.2.1.1. Geographic Variations ............................................................................................................ 12

2.2.1.2. Temporal Variations ............................................................................................................... 14

2.2.2. Modelation of the Wind Pattern in a Certain Area ..................................................................... 14

2.3. Wind Power Production ............................................................................................... 17

2.3.1. Output Power of a Wind Turbine ................................................................................................ 17

2.3.2. Grid Integration .......................................................................................................................... 18

3. Hydropower ............................................................................................................. 19

3.1. Overview on Hydropower Systems ............................................................................... 19

3.1.1. General Status............................................................................................................................. 19

3.1.1.1. Worldwide .............................................................................................................................. 19

3.1.1.2. In Portugal .............................................................................................................................. 21

3.1.2. Future Prospects ......................................................................................................................... 22

3.2. Hydropower Stations ................................................................................................... 23

3.2.1. Their Role .................................................................................................................................... 23

3.2.2. Hydropower Production ............................................................................................................. 24

4. Integration of Wind Power in the Electric System...................................................... 26

4.1. Coordination of Wind Power with other Power Producers ............................................ 26

4.1.1. Hydro Plants ................................................................................................................................ 27

4.1.2. Conventional Thermal Plants ...................................................................................................... 27

4.1.3. Open Cycle Gas Turbine Power Plants ........................................................................................ 27

4.1.4. Combined Cycle Gas Turbine Power Plants ................................................................................ 28

v

4.2. Different Storage Options ............................................................................................ 28

4.2.1. Flywheels .................................................................................................................................... 29

4.2.2. Capacitors ................................................................................................................................... 29

4.2.3. SMES ........................................................................................................................................... 29

4.2.4. Batteries ...................................................................................................................................... 29

4.2.5. CAES ............................................................................................................................................ 30

4.2.6. Hydrogen .................................................................................................................................... 30

4.2.7. Hydro Pumping Plants (HPPs) ..................................................................................................... 30

4.2.8. Summary ..................................................................................................................................... 30

4.3. The Portuguese Framework on Wind-Hydro Coordination ............................................ 33

5. Wind-Hydro Coordination in a Portuguese Production-Load Scenario ....................... 35

5.1. Introduction ................................................................................................................ 35

5.2. Assumptions ................................................................................................................ 36

5.2.1. Historical Data from the year 2007 ............................................................................................. 36

5.2.2. Technical characteristics of the power producers involved in the coordination process .......... 37

5.2.2.1. Wind Parks .............................................................................................................................. 37

5.2.2.2. Hydro Pumping Plants ............................................................................................................ 39

5.2.2.3. Thermal Plants ........................................................................................................................ 41

5.2.3. Hydro Pumping Plants Modelling ............................................................................................... 42

5.2.4. Wind Parks Modelling ................................................................................................................. 43

5.3. Structure of the Algorithm ........................................................................................... 44

5.3.1. Data presentation ....................................................................................................................... 44

5.3.2. Creating different wind scenarios ............................................................................................... 45

5.3.3. Wind-Hydro Coordinated Operation .......................................................................................... 47

5.3.3.1. Pumping mode of operation .................................................................................................. 48

5.3.3.2. Generating mode of operation ............................................................................................... 50

5.3.3.3. Matching power production with demand ............................................................................ 51

5.3.3.3.1. One HPP as a generator ................................................................................................... 52

5.3.3.3.2. Both HPPs as generators .................................................................................................. 52

5.3.3.3.3. Both HPPs stopped ........................................................................................................... 53

5.3.3.3.4. One HPP pumping ............................................................................................................ 53

5.3.3.3.5. Both HPPs pumping .......................................................................................................... 53

5.3.3.3.6. Closing Remarks ............................................................................................................... 53

6. Results ..................................................................................................................... 55

6.1. Performed Simulations ................................................................................................ 55

6.2. Results for different values of the Aggregate Target Power ........................................... 56

6.2.1. Wind Installed Capacity of the year 2007: 2.446MW ................................................................. 56

6.2.1.1. Aggregate Target Power: 500MW .......................................................................................... 57


6.2.2. Wind Installed Capacity of the year 2009: 3.566MW ................................................................. 60



6.3. Discussion of the Results .............................................................................................. 63

6.3.1. Aggregate Target Power: 500MW .............................................................................................. 63

vi

6.3.1.1. Wind Installed Capacity: 2.446MW ........................................................................................ 63


6.3.2. Aggregate Target Power: 750MW .............................................................................................. 65



7. Conclusions .............................................................................................................. 68

7.1. Final Considerations .................................................................................................... 68

7.2. Future work ................................................................................................................. 69

References ...................................................................................................................... 71

Appendix A ..................................................................................................................... 73

Appendix B ..................................................................................................................... 74

B.1 – Results for a wind capacity of 2.446MW and a target power of 500MW ........................................... 74




vii

List of Figures

Figure 1 – New installed capacity per year in Europe [5]. ....................................................................... 3

Figure 2 – Installed capacity of thermal plants, hydro plants and other renewables [6]. ........................ 4

Figure 3 – Evolution of the energy demand and of the contributions of different technologies [6]. ........ 5

Figure 4 – Evolution of the World Total Installed Capacity over the last ten years [7]. ........................... 8

Figure 5 – New Installed Capacity in every year of the last decade [7]. ................................................. 8

Figure 6 – Wind Power Capacity in the 10 leading countries [7]............................................................. 9

Figure 7 – Top 10 countries shares of total installed wind power capacity in 2009 [7]. .......................... 9

Figure 8 – Achieved and predicted development for the total installed wind capacity from 1997 to 2020, [7]. ................................................................................................................................................ 11

Figure 9 – European onshore wind resources at 50meters and for five different topographic conditions [12]. ........................................................................................................................................................ 13

Figure 10 – European offshore wind resources for five different heights above sea level [12]. ........... 13

Figure 11 – Wind speed at a 60meters height [13]. .............................................................................. 14

Figure 12 – Wind power density at a 60meters height [13]. .................................................................. 14

Figure 13 – Representation of a Weibull’s PDF [14]. ............................................................................ 15

Figure 14 – Scale parameter c [m/s] of Weibull probability function at a 60meters height [13]. ........... 16

Figure 15 – Shape parameter k of Weibull probability function at a 60meters height [13]. .................. 16

Figure 16 – Real and theoretical power curves for a 2MW wind turbine. ............................................. 18

Figure 17 – Evolution from 1971 to 2007 of hydro production by region [17]. ...................................... 20

Figure 18 – General situation of hydro potential and external dependence in several countries and target values for Portugal for the year 2020 [19]. .................................................................................. 23

Figure 19 – Typical capacity and power ranges of different storage systems [24]. .............................. 32

Figure 20 – Parameter c [m/s] of Weibull probability function at a 60meters height. ............................ 38

Figure 21 – Parameter k of Weibull probability function at a 60meters height. ..................................... 38

Figure 22 – Results for a target power of 500MW and a wind capacity of 2.446MW, when considering the upper reservoirs initially at 100% of their storage capacity. ............................................................ 57

Figure 23 – Results for a target power of 500MW and a wind capacity of 2.446MW, when considering the upper reservoirs initially at 75% of their storage capacity. .............................................................. 58











viii

List of Tables

Table 1 – Characterization of wind energy production in Portugal since 2001 [9]. ............................... 10

Table 2 – Hydropower installed capacity of the top 10 countries [17]. .................................................. 20

Table 3 – Top 10 countries in hydropower production [17]. .................................................................. 20

Table 4 – Hydropower contribution in the top 10 producers [17]. ......................................................... 20

Table 5 – Evolution of the Portuguese hydropower system from 2001 to 2009 [9]. ............................. 21

Table 6 – Summarised overview of technical characteristics of storages [23]. ..................................... 31

Table 7 – Investment costs of the different storage options, [23] and [24]. .......................................... 33

Table 8 – Summarized characteristics of the six hydro pumping plants, [25]. ...................................... 33

Table 9 – Wind power characteristics: parameters of Weibull function, installed capacity and energy production. ............................................................................................................................................. 38

Table 10 – Time interval during which hydro pumping stations can pump water to the upper reservoir, [26]. ........................................................................................................................................................ 39

Table 11 – Technical characteristics of the pumping hydro stations running in Portugal in 2007. ....... 40

Table 12 – Technical limitations of the equipments on the hydro pumping stations. ............................ 41

Table 13 – Technical Characteristics of the Thermal Plants working in 2007, [26]. ............................. 42

Table 14 – Typical values of the roughness length z0, [11]. .................................................................. 73

Table 15 – Results obtained with the upper reservoirs initially at 100% of their capacity, for 2.446MW of wind capacity and 500MW of target power. ...................................................................................... 74

Table 16 – Results obtained with the upper reservoirs initially at 75% of their capacity, for 2.446MW of wind capacity and 500MW of target power. .......................................................................................... 74











ix

Abbreviations

CAES Compressed Air Energy Storages

CDF Cumulative Distribution Function

ENE2020 National Energy Strategy 2020

GW Gigawatt

GWh Gigawatt hour

hm3 Cubic hectometer

HPP Hydro Pumping Plant

IEA International Energy Association

IHA International Hydropower Association

INETI Instituto Nacional de Engenharia, Tecnologia e Inovação

kW kilowatt

kWh/m3 kilowatt hour per cubic meter

m meter

m/s meters per second

m/s2 meters per second squared

m3/s Cubic meter per second

MW Megawatt

NAS Sodium Sulphur (Batteries)

OECD Organisation for Economic Co-Operation and Development

PDF Probability Density Function

PNBEPH Plano Nacional de Barragens de Elevado Potencial Hidroeléctrico - National Program of Hydropower Dams with High Hydroelectric Potential

SMES Superconducting Magnetic Energy Storages

SNIRH Sistema Nacional de Informação de Recursos Hídricos

TWh Terawatt hour

UNFCCC United Nations Framework Convention on Climate Change

W Watt

W/m2 Watt per square meter

WWEA World Wind Energy Association

€/kW Euro per kilowatt

1

1. Introduction

In this chapter the subject of this thesis is introduced, enhancing the reasons that motivated this

study. The objectives to be achieved in this work are also presented as well as the outline of the

structure of the thesis.

1.1. Historical Background

In the 18th century, the Industrial Revolution, started in England, was the beginning of the huge

development that societies met until these days. People who lived in small villages moved into big

towns to improve their quality of life. These large concentrations of people together with the

developments in industry and in transports, which introduced massively the combustion of fossil fuels,

became the main factors that led to the risky situation we are in today in what concerns to climate

changes.

For decades, people were unaware of the limitations on the existing reserves of fossil fuels and

their implications on the climate, therefore through those years their consumption was unconscious

and abusive. This had severe implications on the current low availability of these energy resources

and also on the levels of high air pollution through the emission of greenhouse gases and other

pollutant particles.

The growing concentration of greenhouse gases in the atmosphere, resulting from human

activities, such as burning fossil fuels or deforestation, is being indicated as the major responsible for

climate changes recorded on Earth in recent years, specially global warming. To counteract this

negative situation, most countries embraced an effort to reduce the emissions of these greenhouse

gases. In 1994 entered into force an international treaty – the United Nations Framework Convention

on Climate Change (UNFCCC) – that was ratified by 193 countries.

In 2005 those countries agreed to apply an addition to the treaty: the Kyoto Protocol. While the

Convention encouraged industrialised countries to stabilize greenhouse gas emissions, the Protocol

commits them to do so by the application of legally binding targets that must be fulfilled. Since the

developed countries are the major responsible for the current high greenhouse gas emissions these

targets are applied to each nation under the principle of “common but differentiated responsibilities”,

with heavier burdens on developed countries [1]. The goal is to reduce global emissions of

greenhouse gases by 5% against the levels in 1990 over the five-year period 2008-2012.

The goal of stabilizing the emissions of greenhouse gases promoted renewable energy

production sources to a capital role since they allow reducing the burning of fossil fuels to produce

electricity. To achieve the targets set to Portugal under the Kyoto Protocol, the Portuguese

government is applying, among other measures, a policy to promote investment in new renewable

energy power plants such as wind parks, hydro or solar power plants.

2

The diversification of energy production sources is of major importance because a country with

no energy reserves cannot be exclusively dependent on the importation of fossil fuels. Therefore,

under the National Energy Strategy 2020 (ENE2020) [2], the Portuguese government recently

presented new targets for the different technologies of production of electricity using renewable energy

sources. These new targets represent an update for the ones presented in 2007 [3].

The referred new targets are as follows:

Wind Power: By the year 2012, additional 2.000MW will be installed in new wind parks and

400MW by upgrading existing wind parks achieving a total installed capacity superior to 5.000MW; it is

also expected that until the year 2020 further 3.000MW of wind capacity will be installed depending on

the evolution of the power demand, on the penetration of electric vehicles, among other factors;

Hydropower: Reinforcement of the rated power of current hydroelectric infrastructures and

installing new hydropower facilities to achieve a 70% rate of exploitation of national hydroelectric

generating capacity potential in the medium term, with an installed capacity of 8.600MW in 2020;

Biomass: To complete the installation of the 250MW already assigned and to establish policies

to promote the production of biomass;

Solar: The fact that solar energy is available during the hours of higher power consumption led to

the set a target of 1.500MW for the installed capacity by the year 2020, which will be composed by

solar photovoltaic and solar thermal systems;

Wave Power: Creation of a pilot zone for the technological development of new prototypes to

support the ambition of having an installed capacity of 250MW by the year 2020;

Biofuels: To achieve a target of at least 10% of biofuels to be incorporated in road fuels by the

year 2020 (following the European Union’s objective);

Biogas: A target of 100MW of installed rated power in units for anaerobic waste processing;

Geothermal: New investments in this area to install further 250MW until the year 2020;

Hydrogen: To explore the potential of hydrogen with the development of the fuel cell

technologies and with the promotion of the integration of hydrogen in the transport sector;

Microgeneration: To promote the installation of 50.000 systems, by 2020, encouraging the

installation of solar hot water in buildings.

The measures and targets listed above are integrated in the ENE2020 that pretends to achieve,

in 2020, a share of 60% of the electricity produced and a share of 31% of the final energy

consumption both based on renewable energy sources [4]. This national strategy is important not only

to help Portugal to fulfil its international obligations of reducing greenhouse gas emissions, due to the

Kyoto Protocol, but also to allow Portugal to be less dependent on the importation of energy resources

like fossil fuels (coal, oil or natural gas) that are an important share of the external debt.

1.2. Renewable Energy Sources

The current global concern about the climate changes bro

spotlight. All over the world, countries are investing in new ways to produce electric energy without

losing sight on environmental concerns.

The countries involved in the Kyoto Protocol in order to accomplish the targe

emissions of greenhouse gases, had to invest in the development of technologies using renewable

energy sources to satisfy their electric power consumption.

2009 of the new installed capacity of

Figure 1. In that period, renewable energy sources had grown from a share of 14% to a share of 61%

of the new installed capacity per

been assuming in the generation of electricity. Since 2008 renewable energy sources have

represented more than 50% of new power installations

power, followed by solar photovoltaic and other renewable technologies such as large hydropower

stations and biomass.

Figure 1

It is also notorious the investment on thermal plants fuelled by natura

use coal or fuel oil to produce electricity. This can be explained by the greater flexibility that thermal

plants powered by natural gas provide t

pollutants resulting from the combustion process

of technology.

3

Renewable Energy Sources – General Overview

The current global concern about the climate changes brought renewable energy sources to the


losing sight on environmental concerns.

The countries involved in the Kyoto Protocol in order to accomplish the targe


energy sources to satisfy their electric power consumption. In Europe, the evolution

of the new installed capacity of the different forms of electrical energy production is presented in

, renewable energy sources had grown from a share of 14% to a share of 61%

year, which demonstrates the relevance that renewable sources have


represented more than 50% of new power installations, being the highest representation for wind


1 – New installed capacity per year in Europe [5].

It is also notorious the investment on thermal plants fuelled by natural gas instead of those that

coal or fuel oil to produce electricity. This can be explained by the greater flexibility that thermal

plants powered by natural gas provide to the electric system, by the lower levels of emissions of

pollutants resulting from the combustion process and mostly by the lower investment cost of this type

General Overview

ught renewable energy sources to the


The countries involved in the Kyoto Protocol in order to accomplish the targets of reducing their


he evolution between 1995 and

the different forms of electrical energy production is presented in

, renewable energy sources had grown from a share of 14% to a share of 61%

year, which demonstrates the relevance that renewable sources have


ighest representation for wind


l gas instead of those that

coal or fuel oil to produce electricity. This can be explained by the greater flexibility that thermal

by the lower levels of emissions of

and mostly by the lower investment cost of this type

4

In Portugal the increasing trend of investing in renewable energy technologies is an effort to

accomplish the targets that Portugal assumed internationally. Before the European Union, Portugal

agreed to have, in 2010, a share of at least 39% of the annual electricity consumption supplied by

renewable energy sources. However, the Portuguese government set an even more ambitious target

raising that share to 45% of the annual energy consumption. Recently this target was raised to 60%

until the year 2020. Under the Kyoto Protocol, Portugal compromised to limit the emissions of

greenhouse gases to a level 27% higher than the level recorded in 1990.

Figure 2 presents the Portuguese evolution of the installed capacity of thermal generation, large

hydro stations and other renewable energy sources in which wind power has the largest share. The

stabilisation on hydropower is temporary since there is a national program of investment in this type of

technology according to which ten new hydro stations will be built until the year 2020. The growing

trend is more explicit in the other renewable energy sources, including wind power, solar photovoltaic

and biomass. The increase in thermal capacity was due to the installation of natural gas plants. It is

also shown in the same figure the evolution of the highest value of peak power demand over the last

five years.

Figure 2 – Installed capacity of thermal plants, hydro plants and other renewables [6].

The evolution of the energy consumed during the last ten years and the contribution of each

generating technology is illustrated in Figure 3. From 2000 to 2009 the annual energy consumed in

Portugal increased more than 10TWh, but in the last three years the annual demand stabilized near

50TWh, and it even decreased in 2009 comparing with 2008, which reflects the effects of economic

crisis.

5

Figure 3 – Evolution of the energy demand and of the contributions of different technologies [6].

Since the installed capacity of large hydropower stations has not increased, its energy production

depends exclusively on the hydrological regime of each year, therefore it varies a lot. The contribution

of wind energy production is the one that has grown the most among all renewable energy sources,

which can be explained by the growing trend of the installed capacity of wind power. Other

technologies using renewable energy sources, such as small hydro, solar photovoltaic or biomass also

increased their energy contribution in the recent years.

According to Figure 3, in the last decade, the import balance of electricity through the

interconnections with the Spanish electric system has experienced an increase. The preference for

importing power instead of generating it in the internal power producers is explained by the lower price

paid to import that energy in comparison to the price that would be paid if inner power producers were

assigned to supply that amount of power. In the near future the power inflow in the interconnections is

expected to decrease due to the investment in new generating facilities with lower operational costs:

new hydropower stations will start operating in the near future, wind power is expected to increase

even more and combined cycle gas power plants are being installed.

1.3. Motivations and Objectives

The wind resource is mainly characterized by its high variability and unpredictability. As wind

speed varies, wind power follows those variations that can occur rapidly, in a time range of seconds or

minutes, as well as in longer time periods of months, corresponding to seasonal variations. This

characteristic of volatility of wind power is a problem to its integration in the electric system either due

to stability issues of the whole system and due to the necessity of global production to always meet

the sum of power demand and losses.

This thesis emerges trying to answer to the problem of integration of wind power production in a

large scale, which is a reality now due to the growth of wind installed capacity. The proposed solution

6

to this issue is the coordination between wind power and hydropower stations equipped with pumping

systems that can accommodate the variations in wind production.

The main purpose of this work is to study the possibility of firming the output power production of

the total wind power installed capacity in Portugal. To do so, the hydropower plants assigned to this

coordination role must operate as pumping stations when the wind power production exceeds a

previously established value, storing that surplus of energy in form of water in their upper reservoirs. In

periods of low wind production, hydropower stations must use the stored water to produce electricity in

order to compensate the lack of wind production. This solution intend to mitigate the unpredictability

and variability of wind creating a perfectly controllable power producer that assures that a certain

amount of power is supplied throughout the whole year.

1.4. Structure of the Thesis

The main purpose of this work is to study the possibility of coordination between wind and hydro

power production; therefore these two technologies will be specially focused. Each one of these

energy production technologies has one dedicated chapter and then there is another chapter that

approaches the coordination between them.

Thus, the structure of this thesis is organized as described next:

In Chapter 2 an overview on wind power progress is provided. We also characterise the wind

resource and its modelation in order to simulate the operation of a wind turbine. The issues regarding

the integration of wind power production in the electric systems are approached too.

In Chapter 3 is analysed the evolution of hydropower worldwide and particularly in Portugal,

enhancing its role in the electric system and the benefits they provide to societies. The expression that

represents the output power of a hydropower station is explained.

In Chapter 4 are studied the different solutions of controllable power plants for coordination with

wind power and the available solutions for storing wind power.

In Chapter 5 is described the algorithm developed in this work to simulate the coordination

between wind and hydropower with the aim to firm the output power of this aggregate.

In Chapter 6 are presented and analysed the results of the simulations performed under this

work.

In Chapter 7 are presented the conclusions and the possible further work to be done in this

subject.

7

2. Wind Power

In this chapter we will run through several aspects of wind power that give the reader a global

perspective of its evolution over the last years. Here will also be focused some technical aspects of

wind power that were particularly important to the development of this study.

2.1. General Situation

Climate changes have been a widely discussed topic either in a political level as in a scientific

level. Despite the obvious damages on the environment, these crises usually have a positive impact in

the technological development of societies due to their effort to mitigate those hazards. In this context,

societies all over the world are investing on the development of energy production using renewable

energy sources. Among the different sources of renewable energy production wind power is the one

with the fastest growth rate, where most of the investment is being made.

2.1.1. Context and Background

2.1.1.1. Worldwide

In order to fulfil the goals established by every nation under the Kyoto’s Protocol the investment

on the development of wind power technology has increased widely over the last years. The installed

capacity of wind power worldwide doubles every three years, which represents a predicted value of

203.500MW by the end of 2010 while in 2009 the capacity was 159.213MW according to [7].

In Figure 4 can be seen this evolution of the wind power capacity through the last decade.

Accepting the prediction of WWEA (World Wind Energy Association) for the year 2010, it is roughly

the double of the installed capacity in 2007, as the value of 2009 is approximately twice the value of

2006. The evolution recorded between two subsequent years has also shown an increasing growth in

the same period. Since 2001, every year, the new installed capacity is higher than it was in the

previous year - Figure 5.

8

Figure 4 – Evolution of the World Total Installed Capacity over the last ten years [7].

Figure 5 – New Installed Capacity in every year of the last decade [7].

The growth of wind power capacity is expected to increase even more in the future since 85,8%

of the total installed capacity in 2009 was spread in only ten countries, being their installed capacity

represented in Figure 6 and in percentage of the total value in Figure 7. As other nations intensify

efforts investing more in wind power and the whole world recovers from the effects of the economic

crisis this technology will experience an even bigger development.

The major constraint for the feasible installation of a wind park is the availability of wind in that

area and how regular and intense it is. Due to all the intermittency and irregularity inherent to wind’s

nature the amount of energy produced by wind turbines is limited. In 2009 all wind turbines installed

worldwide generated 340TWh which represents only 2% of the global electricity demand. However, in

some countries the wind power penetration in the electric system has already reached much higher

9

levels, becoming one of the largest electricity sources. The highest shares of energy produced by wind

power were in Denmark (20%), Portugal (15%), Spain (14%) and Germany (9%), [7].

Figure 6 – Wind Power Capacity in the 10 leading countries [7].

Figure 7 – Top 10 countries shares of total installed wind power capacity in 2009 [7].

2.1.1.2. In Portugal

The first wind turbine installed in Portugal was connected to the grid in 1985, with an installed

capacity of 20kW, [8]. Since then, wind power capacity has grown with such a fast rate that after

almost 25 years the installed capacity has reached 3.566MW. This evolution was a result of several

factors such as the awareness of the advantages that renewable energies like wind power could bring

in the environmental context. The promotion for the installation of new wind farms was mainly done by

the application of a feed-in tariff that assured the wind farm owners that all their energy production

10

would be bought for a fixed price for a period of 10 to 15 years. After this period, the energy produced

by these wind farms must be sold in the electricity market.

When in the market, the wind producers must provide in advance an hourly forecast of their

power production. Due to the volatility of wind speed the predictions done earlier may have a high

error associated. Thus, the wind producers can readjust their predictions although they must pay a

penalty that will reduce the value at which wind power is sold.

In Table 1 are shown the values of installed capacity from 2001 to 2009, as well as the energy

production in each one of those years. During that period the mean annual growth rate was 53,8% for

the installed capacity and 54,4% for the produced energy.

There can also be seen the equivalent hours of production which relate the energy production

with the installed capacity of wind power. These values of equivalent hours consider that all the wind

turbines were already installed at the beginning of the year and therefore they contributed to the

energy production. However, the wind installed capacity of each year was installed during that year,

which results in a higher contribution to the energy production of the firstly installed wind turbines.

Taking as an example the values for 2009, which assume that all the wind turbines totalizing

3.566MW were installed in the beginning of the year: in order to generate 7.740GWh, that wind

installed capacity would have to be generating at their rated power for 2.170 hours.

Table 1 – Characterization of wind energy production in Portugal since 2001 [9].

2001 2002 2003 2004 2005 2006 2007 2008 2009

Energy Production [GWh] 239 341 468 787 1.741 2.892 4.007 5.720 7.740 Installed Capacity [MW] 114 175 253 537 1.047 1.681 2.446 3.012 3.566 Equivalent Hours [hours] 2.090 1.956 1.848 1.465 1.663 1.720 1.638 1.899 2.170

The report [7] published by the WWEA for 2009 indicates Portugal as the ninth country with more

wind capacity and as the second country with the largest share of wind energy produced in a year

(around 15%). As the installed capacity increases it is expected the share of production of wind power

to increase too, which is a desirable thing due to its environmental benefits. However, the large

integration of wind power might become a problem because its intermittency and unpredictability

would make it more difficult to match global generation with demand.

2.1.2. Future Prospects

Although wind power has shown a strong development since its take off, it is expected that its

greatest development will happen in the near future as a result of the investments to be made in the

leading countries but especially in the countries that started later the installation of wind power. China

is an example of one of the countries that is experiencing a enormous development on wind power

11

which can be translated in a growth rate of 113,0% from 2008 to 2009, increasing its installed capacity

from 12.210MW to 26.010MW [7].

The willingness to invest in wind power is a result of the increasing awareness of the social and

environmental benefits that it adds to societies. An improve of the global financial situation

accompanied by incentives to the installation of wind turbines, such as the feed-in tariffs, must result in

a boost to the installation of new wind farms. The WWEA, based on these factors, expect an

exponential growth for the wind capacity worldwide, announcing that by the end of the year 2020 the

global installed capacity may be at least 1.900.000MW, [7]. In Figure 8 is represented the evolution of

the wind capacity from 1997 to 2009 and the prognosis for the further development until the year

2020.

Figure 8 – Achieved and predicted development for the total installed wind capacity from 1997 to 2020, [7].

In Portugal the increasing growth of the wind capacity may not follow the global trend illustrated in

Figure 8. The main reason is that the best areas to install wind farms due to their favourable wind

characteristics are becoming saturated and therefore there are not many places left for a viable and

profitable installation of wind farms. As these windy regions get completely occupied by wind turbines

the solutions for a continuous growth of the installed capacity might be the installation of wind farms in

other less viable places, the substitution of the older wind turbines for new ones with a higher nominal

power or the installation of offshore wind farms, which has already been done in other countries.

2.1.2.1. Offshore Wind Turbines

Installing wind turbines in the sea has serious advantages in comparison to their installation

onshore. In the sea wind speed is more constant and more intense since it suffers less the influence of

friction or topography. This allows offshore wind farms to produce more energy than an equivalent one

onshore. As well, offshore wind turbines do not have a visual impact and are better accepted by public

opinion. However, the installation of wind turbines offshore raised new engineering challenges such as

the fixation of the wind turbines to the bottom of the sea or the transmission of the generated power to

12

the mainland electric grid. Among all the renewable energy sources, offshore wind farms are pointed

as the one with highest potential of development, [10].

The leading country in the installation of offshore wind turbines is the United Kingdom with a total

capacity in 2009 of 688,0MW followed by Denmark with 663,6MW which installed 237,0MW only in

2009.

In Portugal the possibility of installing offshore wind farms is being studied by the analysis of the

offshore potential along the coast line. According to [10] the offshore potential in Portugal could reach

2.500MW with an equivalent utilisation of more than 2.700 hours per year. Allied to the investment in

these developing wind technologies it is also necessary to invest in the reinforcement of the electric

transmission grid to allow this energy to be transferred to the areas where it will be consumed.

2.2. The Wind Resource

The usage of renewable resources to produce electricity has become a global practice worldwide.

As wind is available everywhere, with higher or lower intensity and frequency, its energy can be used

in a profitable way to produce electricity. This helps to explain how wind power production was already

spread to 82 countries worldwide until the year 2009.

2.2.1. Wind Characteristics

In this subsection will be described and analysed some characteristics of wind that have the most

relevance to the production of electricity in general and in particular to the simulations performed in

this work.

2.2.1.1. Geographic Variations

Due to the relative positions between the Earth and the Sun, equatorial regions are more

exposed to the solar radiation than polar regions. This results in a pressure differential between these

regions that leads to the movement of masses of air creating wind.

The installation of a wind turbine in a certain area must be preceded by a period of at least three

years for the evaluation of its wind potential, during which several series of wind speed data are

recorded, [11]. In order to shorten this evaluation period was firstly made in Europe an effort to map

the annual mean wind speed (m/s) and the power density (W/m2) over land and sea. In Figure 9 is

represented the European Wind Atlas, while in Figure 10 is shown the distribution of the wind

resources over open sea. The European Wind Atlas is currently included in a global Atlas that

pretends to map the wind resource worldwide [12].

13

The areas with the highest wind potential are in the north of the United Kingdom both in onshore

and offshore. In opposition, southern France and northern Italy have the lowest wind potential

onshore.

Figure 9 – European onshore wind resources at 50meters

and for five different topographic conditions [12].

Figure 10 – European offshore wind resources for five

different heights above sea level [12].

The Portuguese interest in wind power led to the necessity for a deeper knowledge of the wind

resource in Portugal. In this context, a study of the wind power potential in Portugal was performed.

Measurements of the wind speed in different stations and at different heights all over the country were

carried, resulting in the Portuguese Wind Atlas.

In this study several characteristics of wind were analysed. The mean wind speed and the power

density at a height of 60meters are represented in Figure 11 and Figure 12, respectively. In Portugal,

the wind potential is higher along the western coastline and in some areas in the interior north of the

country where the mean wind speed can reach values around 6,5m/s at a height of 60meters.

14

Figure 11 – Wind speed at a 60meters height [13].

Figure 12 – Wind power density at a 60meters height [13].

2.2.1.2. Temporal Variations

Besides the variations of wind from one region to another, wind also varies in time. These

variations can be recorded by monitoring the output of an anemometer that is a device designed to

measure wind speed.

Wind speed varies in short time periods, from seconds to a few minutes, as well as in longer

periods like days or months. The short time variations are commonly related with turbulence, against

which wind turbines must be projected to resist. Long term variations of wind speed can be related

with the difference in exposition to solar radiation in a daily scale or in a monthly scale. In the first case

the wind speed changes within a daily pattern, while in the second case it varies seasonally.

As wind turbines respond only to wind speed variations longer than turbulence, due to their

inertia, one can consider hourly average values of wind speed as the useful component for energy

production. Equation (1) represents this wind speed modelation as �� is the mean wind speed over an

hour and �� is the turbulence [11].

�� (1)

2.2.2. Modelation of the Wind Pattern in a Certain Area

To evaluate the wind potential of a certain area it is necessary to measure wind speed regularly

during a period as long as possible, ideally it should be three years to record the inter annual

variations [11]. The values recorded by the anemometer are the mean value of wind speed within an

15

hour, considering that the values that lay in an interval with a range of 1m/s are rounded to the nearest

integer number. The measures must be made in the area where the wind turbines are supposed to be

installed and at the height of the rotor.

Due to the high number of wind speed values recorded a probabilistic approach can be used to

describe the wind behaviour. By plotting the occurrence frequency of each wind mean hourly speed it

can be seen that the Weibull probability distribution is the one that fits it better. In equation (2) is

shown the probability density function (PDF) of a Weibull random variable. In this case the variable is

the mean wind speed over an hour in m/s, ��. In the following equation is a scale parameter, in m/s,

and � is a shape parameter, dimensionless.

��

�� (2)

The shape of the PDF of a Weibull distribution with the parameter � 7�/� and parameter � � 2

is represented in Figure 13 (the scale parameter is called � in the figure).

Figure 13 – Representation of a Weibull’s PDF [14].

The cumulative distribution function (CDF) of the Weibull distribution is described by equation (3)

and it is used to calculate the probability of the wind speed to be lower than a certain value.

�� 1 � �� (3)

Since the Weibull distribution can describe probabilistically the pattern of wind speed in a certain

area, we can say that the wind pattern of every region of interest can be represented by the

parameters of a Weibull distribution. In Portugal, INETI mapped the Weibull parameters across the

Portuguese continental territory as represented in Figure 14 and Figure 15.

16

Figure 14 – Scale parameter c [m/s] of Weibull

probability function at a 60meters height [13].

Figure 15 – Shape parameter k of Weibull probability

function at a 60meters height [13].

As the values of the Weibull parameters were set for a height of 60metres the wind speed values

associated must be corrected to the height of interest, meaning the height at which the rotor of the

wind turbines will be positioned.

The topography or the terrain and the obstacles that wind faces in its movement affect its flowing

speed in the intensity and direction. However, these influences are not considered in this study since it

would require the use of flowing models to model the turbulence.

Due to the friction of wind against the surface of the terrain its speed is lower next to the ground

and increases with the height. The range of heights that matter for the project of wind farms goes to

around 100metres and within it the variation of wind speed with the influence of ground friction can be

described by the Prandtl Logarithmic Law, equation (4), in which �� is the mean wind speed at

metres height, �! is called the friction speed, � is the von Kármán constant (equal to 0,4) and " is the

roughness length in the current wind direction that is a characteristic of the region in study, [11].

�� !� ln "� (4)

This expression is important because it allows extrapolating the values of wind speed known at a

certain height, �, to a different height %, using equation (5), [11]. However, this equation assumes

that the surface is flat and uniform and that the roughness does not change; moreover, it does not

consider the influence of topography and obstacles in wind speed. Thus, the values for wind speed

obtained from the extrapolation using equation (5) may have a significant error associated.

17

�� %� �ln� � "�ln� % "�

(5)

2.3. Wind Power Production

The energy produced by a wind farm depends on the wind resource available and on the installed

capacity of the wind turbines. On the following we analyse the power production of a wind turbine and

the integration of this electricity in the electric system.

2.3.1. Output Power of a Wind Turbine

Wind speed is the major factor that affects the power production of a wind turbine. If there is a

high availability of wind, the wind turbine can operate at the rated power or near it maximizing the

power production. However, a wind turbine does not produce electricity for every value of wind speed.

For low values of wind speed the available power in the wind is not very high, therefore it is not viable

to explore the wind turbines in those regimes. That lower limit of wind speed, below which wind

turbines do not operate, is called the cut-in speed that is usually around 5m/s. On the other side there

is also an upper limit of wind speed, above which wind turbines do not work too. If the wind speed is

too high, above the cut-out speed that is usually around 25m/s, the wind turbine is stopped to prevent

it from suffering physical damages – it is a safety practice.

The other value of wind speed that is relevant is the rated wind speed above which the output

power of the wind turbine is regulated to the rated power. This is justified by the increase of

investment that would be needed to strengthen the structure of the wind turbine to support higher wind

speeds that would rarely occur.

In this work the power curve used to represent a wind turbine of 2MW was a theoretical one that

is described by equation (6). In this expression the wind speed comes in m/s and the output power of

the wind turbine in MW.

&�� '()* �+,-,.0, � 1 4cos � 611 � 7611� � 1, 4 7 � 1 152, 15 7 � 1 250, � 9 25

: (6)

To validate this analytical expression for the power curve it is plotted in Figure 16 against a real

power curve of a 2MW wind turbine, which was obtained in a Vestas catalogue [15]. These curves

differ on the rated wind speed. In the Vestas power curve the rated wind speed is 16m/s while in the

theoretical curve this value is 15m/s.

18

Figure 16 – Real and theoretical power curves for a 2MW wind turbine.

As it can be seen in Figure 16, the theoretical expression from equation (6) has a similar shape to

the power curve of the Vestas V80-2MW wind turbine; therefore it is a good approximation.

2.3.2. Grid Integration

The major challenges to the integration of wind power production in the electric system are

related with the intermittency of wind and its randomness and with the utmost necessity for balancing

global generation with demand. The schedule of the different power producers is made according to

the forecasts of intermittent generation and in order to produce electricity in a cost effective way: the

first controllable power plants to operate are the ones with the lower operation marginal cost that

operate on regular basis, followed by the ones with the higher cost that only work when it is strictly

necessary due to demand peaks. Therefore, to guarantee the feasible operation of the electric system

in a technical and economical way wind forecasting is of the major relevance.

Since the wind power installed capacity tends to increase in the near future, further investments

in the electric system may be needed to promote the integration of all wind production. As the wind

resource is often available in remote areas away of the centres of high power consumption it may be

necessary to invest in the reinforcement of the transmission grid to allow that wind production to be

consumed where it is needed. Another investment that may have to be made is on the installation of

controllable power plants with a higher flexibility that are able to change their output power production

as wind production changes. Storage systems to accommodate wind power production when it is in

excess are another option to upgrade the electric system.

In chapter 4 a deeper analysis of the integration of wind power in the electric system that

describes the characteristics of other generating facilities and of the available storage options is

carried.

19

3. Hydropower

In this chapter a general overview of the use of water resources to produce electricity is given

focusing on the different types of facilities, on the evolution and characteristics of hydropower plants

and their importance in the electric system and in societies.

3.1. Overview on Hydropower Systems

Around 70% of the Earth’s surface is covered by water making it an available and valuable

endogenous resource. Nowadays some pioneer projects to transform the energy of sea tides in

electricity are being developed although in a small scale. However, the movement of the water in

rivers have been used to the electricity purpose for a long time, with the obvious limitation that those

power generators can only be installed where there are water courses.

3.1.1. General Status

3.1.1.1. Worldwide

Men realized early that the energy associated to the movement of water in rivers could be useful.

Regarding its use to the production of electricity it is currently a mature technology, well spread

worldwide. According to the International Hydropower Association (IHA) it is currently being utilised in

around 150 countries, with 27.000 generating units in 11.000 hydropower stations [16].

In Table 2 can be seen that by the end of the year 2006 the global installed capacity was 889GW:

China was the country with the highest hydropower installed capacity totalizing 126GW, followed by

the United States of America with a capacity of 99GW and in third was Brazil with 73GW.

The energy produced by hydropower stations depend on the installed capacity but also on the

available water resource. Countries with a higher availability of water in their hydrological systems are

more likely to produce electricity from this renewable source on a regular regime through the whole

year. The leading hydropower producer in 2007 was China with a value of 485GWh that corresponds

to 15,3% of the total hydro energy produced worldwide, 3.162GWh. However, the country with the

higher penetration of hydropower production in their electric system was Norway, in which hydropower

was responsible for supplying 98,2% of the whole energy consumed in 2007. Globally, hydropower

production represented 15,9% of the total energy produced worldwide. In Table 3 and Table 4 the

values of energy produced by hydro in each country and its share of the total energy generation are

presented (** in Table 4 the value 13,5% referring to the rest of the world excludes the countries with

no hydro production).

20

Table 2 – Hydropower installed

capacity of the top 10 countries [17].

Table 3 – Top 10 countries in

hydropower production [17].

Table 4 – Hydropower contribution in

the top 10 producers [17].

Looking back in time and analysing the evolution of the energy produced by hydropower stations,

one can see in Figure 17 that it follows a growing trend. The hydropower production more than

doubled from 1971 to 2007, increasing from 1.295TWh to 3.162TWh.

Figure 17 – Evolution from 1971 to 2007 of hydro production by region [17].

In the year 1973 most of the hydro production (71,6%) was responsibility of OECD members

while in 2007 their share was reduced to 42,2%. This reduction, as well as the increase of the total

hydro production, was mainly due to the increasing weight of China and other Asian countries. They

21

represented together, in 1973, 7,2% of the global hydro production and increased their share to 23,5%

in 2007 [17].

3.1.1.2. In Portugal

The first hydropower station built in Portugal that used the movement of water from a river to

produce electricity dated from the end of the 19th century. In these early years of hydro production

these facilities with capacities limited to a few hundred kW were built without a global strategy of

development and were used to supply local loads.

Around the year 1940 a planned strategy to promote the development and industrialization of the

country led to the installation, in the following years, of big hydropower stations with high storage

capacity. In 1960 hydropower represented 80% of the total installed capacity in Portugal and 95% of

the energy consumed [18]. Due to the growth of power consumption and after the oil crisis in the 70s

hydropower gained a new relevance in Portugal and more hydro stations were built.

In the late years, Portugal embraced a policy of investment in renewable energy sources for

electricity production in order to reduce its dependency on the importation of fossil fuels and to be able

to fulfil its international obligations in reducing the emission of greenhouse gases. In this context, new

projects for new hydro plants and to upgrade the installed capacity of the older ones have been made,

resulting in a total installed capacity of hydropower that reached 4.821MW by the end of 2009 as

presented in Table 5.

Table 5 – Evolution of the Portuguese hydropower system from 2001 to 2009 [9].

2001 2002 2003 2004 2005 2006 2007 2008 2009

Energy Production [GWh]

14.240 8.096 15.894 10.053 5.000 11.323 10.351 7.102 8.717

Installed Capacity [MW]

4.263 4.288 4.292 4.561 4.752 4.784 4.787 4.792 4.821

% of Hydro in Total Production

31,3 17,4 33 20,1 9,7 21,5 19,5 13,3 16,5

The reduction verified from 2001 to 2009 in the contribution of hydropower production to the total

production of electricity can be explained by two main reasons. The first is that the energy production

of a hydro plant depends mostly on the availability of water in rivers; therefore in a year with high

levels of precipitation the water resource is more available to the energy production than in a year of

drought. The other reason is the low growth of hydro installed capacity that was mainly compensated

with the exponential increase in wind power and the investment in other renewable sources, such as

photovoltaic or biomass, or in thermal plants fuelled by natural gas.

22

3.1.2. Future Prospects

Hydropower is the renewable energy source with the highest share of energy production

worldwide. However, this share can still be increased since most countries have not exploited fully

their hydro potential. With judicious planning and investment, combined with the potential for

significant growth, hydropower can assume an even more leading role among the renewable energy

sources.

The exponential increase of wind power installed capacity in the electric systems worldwide can

be an enormous stimulus to the growth of hydropower as it is pointed as the best solution to

compensate the intermittency of wind (hydro pumped storage) and to promote its integration in the

electric systems.

Following this trend, the Portuguese government approved a plan of investment in 10 new

hydropower stations – PNBEPH (National Program of Hydropower Dams with High Hydroelectric

Potential). Under this program were evaluated 25 potential hydropower projects among which were

selected 10 according to their economical, operational and environmental viability. The investment on

these hydro plants is based on the knowledge of the unexploited hydro potential available in Portugal,

which was said to be around 54%. This percentage of hydro potential to be explored is determined by

the ratio between the total hydro installed capacity and the theoretical hydro potential. The target set

under the PNBEPH was that in 2020 Portugal will have around 70% of its hydro potential explored

which corresponds to an installed capacity of 7.000MW in opposition to the 5.575MW expected in

2010, [18].

Besides the increase on the installed capacity and on the energy produced by hydro plants, the

installation of new facilities of this type also promote the integration of more wind power capacity in the

electric system allowing it to continue the increasing trend of the last years. When there is wind power

production in excess these hydro plants equipped with pumping systems will store that surplus of wind

production in form of water in the upper reservoir, and will use it to produce electricity in periods of

high demand. At these days, there are already six hydro pumping plants (HPPs) operating in Portugal,

totalizing a pumping capacity that almost reaches 1.000MW. After 2012 this pumping capacity will be

increased to 1.400MW due to the connection of two new HPPs.

Figure 18 presents the situation of some countries in what regards their dependence on external

energy and their unexploited hydro potential, with the aim of understanding in which of these countries

the development of hydropower would be more profitable. It turns out that the Portuguese position is

not favourable at this point with around 85% of external dependence and a high level of unexploited

hydropower, around 54%. In this context, Portugal has a major opportunity to improve its situation by

reducing the dependency on importation of energy resources and exploring better its endogenous

energy resources such as hydro, wind or biomass.

23

Figure 18 – General situation of hydro potential and external dependence in several countries and target values

for Portugal for the year 2020 [19].

Environmental, technical and economical restrictions do not allow all the available hydro potential

to be used: from all the hydro potential of the Portuguese rivers, estimated in terms of energy in

32TWh, only 21TWh could be used [20]. This will lead to a situation in which while more hydro plants

are installed their investment costs will increase due to the lack of viable places with a good hydro

potential.

Apart from this national program, some projects of hydro plants with special features that make

them particularly suitable for operating exclusively in coordination with wind power are being made.

These pumping facilities are composed by two reservoirs, with a modest capacity, placed near each

other in order to minimize the length of the hydraulic circuit but with a difference of heights as big as

possible, so the power consumed during the pumping process is maximized. These hydro stations

may have an important role in the integration of wind power production in the near future, since their

installation is much faster than the installation of a conventional reversible hydro plant, because they

usually use already existing reservoirs.

3.2. Hydropower Stations

In this subsection an overview on the importance of hydropower stations in different situations is

given and the analytical expressions that were used in this work to represent the operation of those

facilities are explained.

3.2.1. Their Role

Depending on the type, the hydropower stations assume a different role in what regards the use

of the water resource. Hydro stations with a big storage capacity are crucial to store water that may be

24

used to different purposes besides the production of electricity: water supply to irrigation of agricultural

fields crucial in periods of drought, flood control, water available to help extinguishing fires or leisure

activities.

On the energy production role different hydro plants have different responsibilities. The hydro

stations with no regulation or storage capacity are used to provide base load since their electricity

production is available whenever there is enough water flowing in the river course. On the other hand,

hydro facilities with storage capacity are used to follow peaks of power demand due to their

controllability and flexible operation. Storage hydro stations, including those with pumped storage

capacity, can improve the performance of conventional thermal plants. As hydro plants follow the rapid

changes in power demand, they allow thermal plants to operate at their optimum steady-state which

can even reduce the consumption of fuel by these thermal plants and extend their lifetime.

As mentioned before, hydro plants with storage capacity also have a crucial role in the integration

of wind power capacity in large scale in the electric systems. The flexibility of this type of power plants

allows them to compensate the rapid changes on wind power production. Hydro pumped storage

systems can use the excess of wind production, in periods of high wind and low power demand, to

move water to the upper reservoirs keeping it available to be used later to produce energy, in periods

of high demand.

The flexible characteristic of hydropower plants is also important to guarantee the security of

supply and the stability of the electric system. In situations of sudden failure in a thermal generating

unit, hydropower stations can rapidly increase their production keeping the balance between global

production and demand.

Another benefit from the use of hydropower instead of using controllable thermal power plants is

the cutback in the emissions of greenhouse gases associated to the operation of these power plants.

3.2.2. Hydropower Production

The power output of a hydropower station depends on the characteristics of the installed

equipment and on the characteristics of the whole structure that feeds them with water (hydraulic feed-

in circuit and on the height of the fall between reservoirs).

The production of electricity is based on the conversion of different types of energy. The water

stored in the upper reservoir has associated an amount of energy (; in Joules) which depends on the

mass of that volume of water (� in kilograms), on the height (< in meters) and on the acceleration due

to gravity (= � 9,81�/�%), according to equation (7).

; � �=< (7)

25

The energy stored, given by equation (7), is converted in kinetic energy as water falls from the

superior reservoir to the turbines through the feed-in circuit. The kinetic energy of the water flow is

transferred to the rotor of the turbine that is coupled with the generator, which will transform the

rotational movement in electricity to be injected in the electric system. The amount of power to be

produced is defined by the regulation of the intake valve that changes the water flow as needed.

The available power in the upper reservoir of the hydro station can be approximately determined

using equation (8), which is obtained manipulating equation (7). Dividing both members of equation (7)

by a period of time, the energy (;) becomes the power (&), in Watts, and the mass (�) becomes the

rate of fluid flow (�@ ), in �=/�.

& � �@ =< (8)

The rate of fluid flow (�@ ) can be expressed as the product of a volume per second, also known as

the flow (A [�B/�]), and the density of the water C (1.000�=/�B) as shown in equation (9).

& � C E A E = E < (9)

Multiplying the density of the water by the acceleration due to gravity, the specific weight is

obtained: F � C E = � 9.810G/�B. In equation (10) is presented the expression used in this work to

estimate the output power of a hydropower station as a function of the water flow rate and of the

height of the fall. The available power stored in the reservoir is affected by an efficiency (HIJKJLMNOKI)

that represents the losses that occur in the feed-in circuit, in the turbines and in the generators.

&'P* � 9.810 E A E < E HIJKJLMNOKI (10)

When the hydropower station operates as a pumping facility the expression used to estimate the

power consumed by the hydro plant is given by equation (11). In this case the efficiency used

(HQRSQOKI) represents the losses in the motors that drive the pumps, in the pumps themselves and in

the hydraulic circuit through which the water is sent to the upper reservoir.

&'P* � 9.810 E A E <HQRSQOKI (11)

26

4. Integration of Wind Power in the Electric System

In this chapter the different options of generating facilities available to operate in a

complementary regime with wind power are reviewed. Subsequently, several solutions for the storage

of wind power are analysed.

4.1. Coordination of Wind Power with other Power Producers

Average variations of load power consumption can be predicted since they follow certain daily or

seasonal patterns. However, instant variations of the load are totally unpredictable because they

depend directly on the consumers’ activity. At every moment the system operator has to guarantee

that global production equals the load including the power losses in the grid. In order to do so, the

operator schedules the power plants to work at a determined time according to forecasts of power

demand and availability of renewable energy resources. To compensate an unpredictable increase in

power consumption and/or a sudden reduction in the production of a generating facility some reserves

are kept in part of some power stations.

The unpredictable variations on power consumption are firstly satisfied by the spinning reserve of

working generators, which increase or decrease their rotating speed as the load decreases or

increases. Since the speed rotation is intimately related with the voltage frequency, which can only

vary within a short interval (±0,1% of the rated value [21]), it is necessary to adjust the production to

the load in a short time period to avoid stability issues. To do so there must be available in the system

some power plants that can rapidly change their output power, either increasing or decreasing it.

These sudden variations on traditional thermal power plants, besides their unlikely feasibility due to

the high thermal inertia of these facilities, have negative impacts on the durability of the equipments.

In addition to the power consumption uncertainty there are other uncertainties that must be dealt

with, such as the ones introduced by renewable energy sources, like wind or solar, that are not

controllable due to their dependence on weather conditions.

The current growth of wind power integration on energy systems is a desirable phenomenon

because it allows reducing emissions of greenhouse gases associated with the operation of fossil-

fuelled power plants. However, depending on the system, this integration is limited by stability issues

that might occur when wind energy penetration is too large. These problems are specially related to

the inherent unpredictability of wind speed variations.

The variability and uncertainty of wind speed, and thus of wind power production, has negative

impacts on the management of the system. From the system point of view it would be better if wind

power production was controllable, or at least its variations attenuated. Some efforts have been made

to attenuate wind speed variations and their effect on the electric system. The easiest solution is to

curtail wind production when it reaches such a high level that the system might become unstable.

However, this is not a desirable solution to the wind farms owners, who see their profit reduced if their

27

production is not injected into the grid, neither to the environment because an amount of energy

produced with no emissions of green house gases (if neglected the emissions associated to the

construction and installation of the wind farms) is being rejected by the electric system.

According to the predictions of load variations and wind power variations, weekly and daily

planning are made to the operation of the generating facilities connected to the grid. The uncertainty

involved in weekly planning of the unit commitment operation schedule, due to the stochastic

behaviour of wind, is about ±25% of the wind installed capacity, with a confidence level around 70%.

The predictions performed one day in advance have an uncertainty of ±15%. Since the unit

commitment is not quite exact, a portion of the work to correct the imbalance may be performed in

electricity markets organized less than one day ahead, [22].

Coordination between wind power and other generation facilities is also a possibility for the

integration of wind production in the electric system. However, as wind experiences short-term

fluctuations new imbalances between load and production will be a constant. Consequently, the other

generators must be able to increase or decrease production very quickly. Not all controllable

generation facilities are suitable for this type of operation. In the following, a short analysis, focusing

on the most important characteristics of the conventional controllable power plants, is done in order to

understand the best options to coordinate with wind power production. This analysis is based on

reference [22] and evaluates the start-up and shutdown capacity of the plant, the output regulation

velocity and the technical minimum load.

4.1.1. Hydro Plants

Hydro plants are the most flexible power plants. They can perform continuous start-ups and

shutdowns without a significant detrimental effect on the equipment’s service life. They can also

change their output power within a few seconds, being possible to vary the power by about 100% per

minute. Another favourable characteristic is their ability to work away from the nominal power,

sometimes less than 10% of the installed capacity.

4.1.2. Conventional Thermal Plants

This type of power plant is the less flexible of the generation facilities. Their start-up and

shutdown capacity is reduced. Due to their thermal inertia the start-up process requires a substantial

amount of energy, which involves a substantial cost and takes a long time. The service life of the plant

is also significantly reduced if continuous start-ups and shutdowns are performed.

The regulation velocity of these plants is limited to about 1% per minute, due to their high thermal

inertia. The technical minimum of this type of plants is about 45% of maximum power.

4.1.3. Open Cycle Gas Turbine Power Plants

28

These power plants are significantly flexible allowing continuous start-ups and shutdowns without

a great effect in the service life of the plant. Its power variations are faster than the ones performed by

conventional thermal, with a power gradient of 4% per minute. However, the technical minimum of this

type of technology is usually about 60% of the installed capacity. This value takes into account the

amount of power that is always necessary to feed the compressors of the power plant.

4.1.4. Combined Cycle Gas Turbine Power Plants

These power plants are more flexible than conventional thermal plants, due to the greater

flexibility provided by gas turbine. However, they are less flexible than open cycle turbines. The

regulation speed of combined cycle gas plants is about 2,5% per minute; higher than conventional

thermal, but slightly lower than open cycle turbines, due to their higher thermal inertia. The minimum

power at which these plants can work is about 50% of the power at full load.

A significant disadvantage of gas plants is the high fuel cost, because it follows the value of oil in

the markets. Thus, conventional thermal plants may produce energy at a lower cost because coal is

usually cheaper than gas.

Based on the characteristics of the options presented here, hydropower plants are the best option

to the coordinated operation with wind parks. Their ability to change the operation point in a matter of

seconds makes them the best solution to follow wind power short-term variations. The operation of a

hydropower facility is also the cheapest option since their fuel cost is zero.

4.2. Different Storage Options

Other solutions that have been developed to help the integration of wind power into the electric

system focus attention on the storage of wind energy production in periods when its injection in the

grid might compromise the stability of the whole system or when the level of power consumption does

not request a lot of production. In order to reduce the impact of wind speed variations on the power

system one could improve wind forecast or on the other hand introduce in the system wind energy

storage. The wind forecast is already much improved by using complex models and historical data,

nevertheless it is still not very exact. A storage facility to be used as a power and energy buffer can

smooth the power output fluctuations from a wind farm and remedy the volatility of wind power [23].

There are already different solutions available to implement as storage facilities, but not all these

solutions are suitable for all type of applications due to their different specificities. Flywheels,

capacitors, superconducting magnetic energy storages (SMES), batteries, compressed air energy

storages (CAES), hydro pumping plants (HPPs) and hydrogen are the most important storage facilities

available to coordinate with wind power. Several characteristics, such as the storage capacity, energy

density, access time, life time, are determinant for the selection of each technology to each case.

29

Some solutions have better performances on storing large amounts of energy for long time periods

(larger than hours); others can only store a reduced quantity for really short time period (fractions of

second).

4.2.1. Flywheels

The energy is stored as mechanical energy by the rotation of the flywheel coupled to a motor-

generator unit connected to the power grid. If there is wind production to be stored the motor is fed by

the electric grid and increases the speed rotation of the flywheel. If, on the other hand, there is a lack

of energy production, the rotational movement of the flywheel will actuate the generator that injects the

generated energy in the grid.

Flywheels are recommended to store wind energy during short time periods due to their self

discharge rate that lies between 1% and 10% per hour. Other characteristics of flywheels are their

long life time, high energy density, large maximum power output, short access time, high efficiency

and small environment impact [23].

4.2.2. Capacitors

The capacitors considered here are also known as super capacitors, because they have a higher

storage capacity compared to conventional ones. These capacitors have a very short access time of a

few milliseconds, and so in that time they can charge or discharge large amounts of power, but not

large amounts of energy. The major drawback of this solution is its self discharge rate which is about

10% per day. Therefore super capacitors are not suitable for long-term storage.

4.2.3. SMES

In this solution the energy is stored as magnetic energy in the magnetic field of a coil. The access

time is very short then a very high power can be discharged within a few milliseconds. However,

SMES are not a viable solution to store energy for a long period of time, because all the stored energy

is released in few seconds.

The environmental impact of SMES depends on the strength of the magnetic field developed by

the coil. For large SMES systems the impact might be significant and moreover there might arise

stability problems caused by the strong magnetic field. Another disadvantage is the small energy

density provided by this solution.

4.2.4. Batteries

Batteries are currently widely used to store electric energy for a large number of applications.

Sodium sulphur batteries (NAS) have been chosen to store large amounts of wind energy because

30

they have large energy density, fast access time, among other favourable characteristics. These

batteries, once connected to the electric grid, can supply the system with a large amount of power for

a short time, or with a large amount of energy for a longer period. If a higher power capacity is

needed, more modules of these batteries can be connected [23].

4.2.5. CAES

This storage solution uses the excess electric energy produced by wind power to store air by

compressing it into underground cavities (artificial or natural cavities). When there is a necessity of

production in the system the compressed air is used to produce electrical energy as it is released from

the pressurised cavity and passes through a turbine that drives a generator. The efficiency of this

storage method is about 42% to 52%. This efficiency can be increased up to 70% using additional

heat storage – adiabatic CAES. The stored heat is later used to warm up the compressed air before it

passes through the turbine [23].

4.2.6. Hydrogen

Hydrogen is the most abundant chemical element; however its presence in nature is almost

always coupled with other chemical elements. The excess wind energy might be used to obtain

hydrogen through an electrolysis process. This hydrogen is then stored into a gas tank and when

needed it can be used in a fuel cell to produce electricity. Another possible use for the stored

hydrogen is as a fuel for vehicles.

The main advantages of this storage option are the large amount of energy that can be stored

and the fact that during the transformation the fuel cell develops pure water and no pollutant

emissions. On the other hand, the major drawback is the efficiency of the whole process that is low,

about 25%.

4.2.7. Hydro Pumping Plants (HPPs)

In this storage solution, wind energy is stored in the form of water in a reservoir. When there is

excess of wind production, the surplus is used to feed pumping systems in the hydro stations that

pump water from a lower to an upper reservoir. Later, when more production is needed to match the

power demand of the system, the water in the upper reservoir is used to drive a turbine coupled with a

generator which produces electricity that is fed to the electric system. The efficiency of the process is

about 75%, and one of the biggest advantages is the large life time of these facilities, which is about

50 years. The major problems related with these stations are the lack of places suitable for the

installation and the huge environmental impact due to their installation.

4.2.8. Summary

31

According to the previous listed characteristics of each solution it can be seen that there are

solutions suitable for short-term power storage and others for long-term storage of energy. Flywheels,

capacitors, SMES and batteries fit better in power applications because they can supply large amount

of power in a very short time. By contrast, CAES, hydro pump storages, hydrogen and batteries,

again, can be used for energy applications due to their ability to supply large amount of energy for a

long time.

In Table 6 are summarised the characteristics of the different storage options and in Figure 19 is

shown their range for power and energy applications. It can be seen in Table 6 that the solutions for

power applications have a lower access time and a higher efficiency. However they also have a

smaller power and storage capacity. Some of these storage solutions ally their lower storage capacity

with the fact that while they are on stand-by their stored power tends to decrease due to the self

discharge characteristic. On the other hand, solutions suitable for energy applications have a larger

power and storage capacity, a longer life time, but a lower efficiency and a longer access time. The

fact that these solutions do not have the self discharging characteristic allows them to store the energy

for a longer period and in bigger quantities.

Table 6 – Summarised overview of technical characteristics of storages [23].

32

Figure 19 – Typical capacity and power ranges of different storage systems [24].

Also the environmental effect of the installation and operation of these storage solutions is an

important concern when investing in one of these facilities. Flywheels are the solution with the lowest

environmental effect while pump hydro stations have the highest effect on the environment. The

installation of one of these stations affects its surrounding area, specially the people who live there

and any other species because the inundated area is usually large and destroys their natural habitat.

However, after the installation of any of these solutions their regular operation on storing and

supplying energy to the electric system does not involve any emissions of greenhouse gases, which is

a major advantage. An intensive study on this subject is always necessary when a storage facility is

being considered, measuring all the environmental advantages and drawbacks of each solution.

The investment costs also differ from a technology to another. These costs depend on several

factors such as the state of the art of the technology, technical improvements (efficiency, life time,

lower production costs...), commercialisation of the technology, position of other storage technologies

(competition), and the environmental impact. In Table 7 are shown the reference values (based on

[23] and[24]) for an investment on a storage facility. These values regard to 2006 and the unit is €/kW

of installed capacity.

Regarding the short-term storage options, SMES is probably the most expensive solution as it is

not a mature technology. On the other hand, batteries are the cheapest one since it is a mature

technology. If considering the long-term storage options hydrogen is the most expensive one while

CAES is the cheapest one.

As storage technologies keep developing their prices are expected to drop, which is a desirable

thing to happen since the high cost of energy storage is the chief reason why it is not more widely

used today. However, on pump hydro stations the investment cost tends to grow due to the lack of

suitable places to install these facilities and due to the increasing environmental effect while suitable

places run lower.

33

Table 7 – Investment costs of the different storage options, [23] and [24].

Storage Option

Flywheel Capacitors SMES NAS

Batteries

Pump Hydro Station

CAES Hydrogen

Investment Cost [€/kW] 150 - 250 200 - 600 (*) 50 - 250 /

2200 (**) 600 500 9000

(*) On reference [24] is not given a value; it is said the price is very high.

(**) If the batteries are designed to a short-term storage (power application) the cost is 50-250 €/kW; on the

other hand, if a long-term storage is required (energy application) the cost would be around 2.200 €/kW.

4.3. The Portuguese Framework on Wind-Hydro Coordination

Nowadays, renewable energy producers are well spread all over the national territory, being the

total wind power capacity of 3.566MW by the end of 2009, and the hydro power capacity of 4.821MW

at the same date [9]. From the total hydro power capacity installed in Portugal, 1.100MW belong to six

hydro power plants equipped with pumping systems, being the pumping capacity almost 1.000MW.

Their characteristics are listed in Table 8.

Table 8 – Summarized characteristics of the six hydro pumping plants, [25].

Hydro Pumping Plants

Watercourse Entry Into Service

Generating Capacity [MW]

Pumping Capacity [MW]

Reservoir Useful Capacity [hm3]

Aguieira Mondego 1981 337,2 273 216 Alqueva Guadiana 2003 259,2 213,8 3.150

Alto Rabagão Rabagão 1964 73,5 63,4 550,1 Frades Rabagão 2005 183,2 183,2 92,1 (*) Torrão Torrão 1988 146 146,6 22

Vilarinho das Furnas Homem 1972 141,3 78,6 69,7

(*) Frades uses as the upper reservoir, the basin of another hydro plant located before it in the watercourse -

Venda Nova.

The newer hydro power plants are equipped with reversible groups that can either work as

turbines, actuating a generator as the water falls from the upper reservoir to the lower one or as

pumps, fed by the electric grid and pumping water in the opposite direction. By the time the older

hydro power plants were built, pumping technology was not being applied to this purpose. Therefore,

the pumping systems in the older hydro power plants were not installed when they were built, but later,

in parallel with the turbine-generator system.

34

The operation experience in using these HPPs led to the operation of Vilarinho das Furnas

almost always as a generating facility, despite it has one group equipped with a pumping system since

1987 [25] [26].

These six hydro power plants have been working since their construction but their pumping

capacity has been used only to accommodate some variations of intermittent production when it is in

excess jeopardizing the balance between production and load, or in situations when it is necessary to

regulate the levels of water in the reservoirs according to the management strategy of those

reservoirs. However the pumping mode of operation is only used when it is economically viable to

pump up water due to a lower price of electrical energy.

The system operator uses several estimations of the wind power available in the system to

schedule the operation of other producers or to keep them connected to the grid as reserves. In

addition, the Portuguese electric system is organised in a way that the energy produced by renewable

energy sources has priority over other controllable generators when to be injected in the grid, due to

the environmental benefits that arise from it. However, wind speed predictions have a lot of uncertainty

associated which means that the reserves kept in part in the system must be increased as the

installed capacity of wind power grows.

In this work a possible solution to overcome the unpredictability and intermittency of wind power

is proposed: the use of hydro plants equipped with pumping systems to control the overall output

power of wind farms at a certain target level, instead of using them only to smooth the wind power

variations. When wind power production is higher than the target level, the surplus of power is used to

feed the pumping systems and water is stored in the superior reservoirs remaining available to be

used later to be converted in electricity, when wind power production is lower than the target value.

The major aim of this coordinated operation between wind and hydro power is to provide the

electric system with a renewable energy producer, free of all the irregularity, which is capable of

supplying the same amount of power every hour of the year.

The economical feasibility of this coordination process is questionable since it depends on the

prices at which electricity to feed the pumping process is paid and on the prices at which wind power

production is sold. Although the economical aspects of the coordinated operation were not a concern

in this study, they were suggested as possible future work on this subject.

35

5. Wind-Hydro Coordination in a Portuguese

Production-Load Scenario

In this chapter, a description of the algorithm developed to study the coordination between wind

and hydro power in a Portuguese production-load scenario, using historical data of the year 2007, is

performed.

5.1. Introduction

The exploitation of hydro pumping plants to accommodate the excess of production is already a

current practice in the Portuguese electric system. In this study, the role of those hydro plants is to

maintain at a certain level the output power production of all wind farms connected to the electric

system. The number of hydro plants assigned to this task was determined based on the installed

capacity of the turbine-generator units and on the target power that is supposed to be maintained

constant. Therefore, Aguieira and Alqueva are the two hydro pumping plants selected since they have

the largest installed capacity: 596,4MW for the generating process and 486,8MW for the pumping

process (Table 8).

The target power to be maintained at a constant value depends on that generating installed

capacity because in periods with no wind production, those hydro plants must be able to supply the

target power.

Since wind production is not controllable and its variations might occur very quickly as wind

speed changes, the hydro plants detached to maintain wind power constant must have a fast

response. If wind production is very high, above the predefined value, it is used to feed the pumping

stations while they pump water from the lower to the upper reservoirs. If, in opposition, the wind power

production is lower than the predefined value, the hydro stations must supply the remaining power to

the grid. Apart from the installed capacity of the equipments, turbines and pumps, this coordination

process has several other limitations, for example: the hydro station can only pump water to the upper

basin if there is water in the lower reservoir and if there is enough available capacity in the upper one;

on the other hand, the hydro station will only generate electricity to compensate the lack of wind power

while it has water remaining in the upper reservoir.

Because electric energy cannot be stored in large quantities or for a long time, in the electric

system the global production has always to match the power load including the grid losses. If an

electric grid is a part of a larger electric system, like the Portuguese grid that is a small part of the

whole European one, there are interconnections with other electric systems that allow the system

operator to import or export power as needed. However, the power flows on the interconnections are

not managed only by one part of the system, but are previously agreed between the several

intervenients and are limited by the capacity of the interconnection lines.

36

According to these assumptions an algorithm was developed. Based upon historical values of

power production and consumption in the different points of the transmission grid, the proposed

algorithm coordinates wind power with two hydro pumping plants and later adjusts the output of the

thermal power plants to guarantee that the correspondence between power generation and demand is

always achieved. The simulations performed by this algorithm use historical values of the year 2007

with a time step of two hours.

5.2. Assumptions

An effort to simulate the coordination between wind and hydro power in a realistic way was made

in this work. Therefore, historical values of power generated or consumed in different points of the

transmission grid, such as substations and power plants, were used. These values are the ones

gathered in [26]. Likewise, the characteristic parameters of the hydro pumping plants, like the rated

power of the pumps or of the turbines, their maximum water flow or the capacity of the reservoirs,

were used. This information is available at the web page of the owner of these facilities, [25].

5.2.1. Historical Data from the year 2007

The simulations performed in this study use as a starting point the production and consumption

power profiles recorded during the year 2007, with a time step of two hours, in several points of the

transmission grid. The values of production or consumption in each two hours are the average values

of the power recorded in those periods and are expressed in MW.

The points of the transmission grid considered include 8 thermal power plants connected to the

grid, 6 hydro pumping stations previously referred, 21 other hydro plants with large installed capacity,

5 wind parks directly connected to the transmission grid and 48 substations, which represent the

interface between the transmission grid and the distribution grid and where other smaller electricity

producers are connected to the electric system. Although these generating facilities are represented

by these several buses, the power demand seen by the transmission grid is all localized in one

equivalent bus.

The power flow in the interconnections between the Portuguese and the Spanish grids is

considered as load to the Portuguese grid. If the recorded value is positive it means that Portugal is

exporting to Spain, therefore that power can be seen as an increase in the global demand. On the

other hand, if the value recorded in the power lines of the interconnection is negative the power is

flowing from Spain to Portugal and it can be seen as an increase in the power production or as a

decrease in the load seen by the Portuguese electric system. This is an important characteristic of this

work, because it is crucial to always keep in mind that we are considering the Portuguese electric

system as an isolated system. Therefore, when the internal balance between production and demand

is compromised the power flow in the interconnections cannot be changed, but must be kept in the

historical values recorded instead.

37

For all the power profiles considered in this work, a positive value refers to a generation of power

in that point of the grid, while a negative value means that in that point of the grid electricity is being

consumed. In the power profile of both hydro pumping stations coordinated with wind power a

negative value indicates that the hydro plant is absorbing power during that period of two hours

because it is pumping water to the upper reservoir.

5.2.2. Technical characteristics of the power producers involved in the

coordination process

The operation of the different power plants in the electric system is primarily influenced by the

technical characteristics of the equipments that compose the facility. For instance, the output power of

a wind park is limited by its installed capacity, or the output power of a hydro plant that is limited by the

head between reservoirs as well as by its installed capacity.

Only the generating facilities that are involved in the coordinated operation between wind and

hydro power are described: firstly the wind parks, secondly the hydro pumping plants and thirdly the

thermal power plants. The technical characteristics of other generating facilities, such as large and

small hydro, are not relevant to this study since for those facilities the historical records of production

profiles were used.

5.2.2.1. Wind Parks

Wind power production profiles used in this study do not follow any historical data from the year

2007. On the other hand, wind production profiles are randomly generated following a Weibull

probability distribution function. To perform these simulations of wind production, the installed capacity

of wind power and the parameters of the Weibull distribution are required.

To consider the geographical variations of wind speed over the national territory, a production

profile is generated for each one of the 18 districts rather than a single wind production profile to the

whole country. To do so, the installed capacity of wind power and the parameters of the probability

function are needed for each district. Figure 20 and Figure 21, reproduced here again, show the

Portuguese national territory and values for the parameters of Weibull probability function in each

region. These values are a result of a work developed by INETI, [13], with the goal of gathering

information about the wind resource available in Portugal.

In Table 9 the values of wind installed capacity per district in the years 2007 and 2009, as well as

the generated energy are shown [9]. Also shown are the values for the parameters of Weibull

probability distribution function which were selected from Figure 20 and Figure 21. The selection of the

values for the parameters of Weibull function involves two steps. The first step was to choose an

approximate value for each district based on the maps of Figure 20 and Figure 21. The second step

was to make a fine adjustment of the selected values aiming to approximately achieve the annual

energy production of the year 2007 in each district.

38

The values of wind capacity of the year 2009 were used for simulations, where the influence of an

increasing wind capacity in the coordinated operation between wind and hydro power was studied. In

those simulations the Weibull parameters presented in Table 9 were used.

Figure 20 – Parameter c [m/s] of Weibull probability

function at a 60meters height.

Figure 21 – Parameter k of Weibull probability function

at a 60meters height.

Table 9 – Wind power characteristics: parameters of Weibull function, installed capacity and energy production.

District c

[m/s] k

[dimensionless]

2007 2009

Installed Capacity

[MW]

Energy Production

[GWh]

Installed Capacity

[MW]

Energy Production

[GWh]

Aveiro 7 1,8 41 85 41 97

Beja 5,5 1,8 0 0 27 52

Braga 6,5 1,5 118 227 151 294

Bragança 7,5 1,3 6 22 73 113

Castelo Branco 5,5 1,5 383 497 470 1.038

Coimbra 6 1,6 269 457 465 900

Évora 5 1,9 0 0 0 0

Faro 7 2,2 38 70 144 237

Guarda 6,5 1,5 84 133 150 366

Leiria 7 2,2 151 288 231 485

Lisboa 7 2,2 203 455 287 683

Portalegre 5,5 1,8 0 0 0 0

39

Porto 5,5 1,5 92 120 105 220

Santarém 7 1,5 137 342 157 396

Setúbal 6,5 2,2 19 28 19 36

Viana do Castelo 6 2,1 351 186 351 704

Vila Real 6,5 1,6 171 387 272 551

Viseu 6,5 1,6 383 710 624 1.268

Total 2.446 4.007 3.566 7.440

5.2.2.2. Hydro Pumping Plants

The experience in the operation of the hydro pumping stations running in 2007 led to some

limitations in the pumping process. According to [26], each of these pumping stations can only pump

water continuously, at the rated power, during a limited time period. Assuming an efficiency of 70% for

the pumping process (HQRSQOKI - which includes the losses in the hydraulic circuit and in the pumping

equipments) and knowing the rated power of the pumps and the head it is possible to determine the

volume of water that is pumped during that time interval. Using equation (12), adapted from equation

(11) to express power in MW, one can calculate the flow A in m3/s. Multiplying the flow A by the time

intervals of Table 10 the capacity of the lower reservoirs is determined. In this equation T is the head,

in meters. The head of the waterfall considered in this work is the mean value between the maximum

and the minimum head allowed by the operation of the hydro plants, which are presented in [25].

&'UP*QRSQOKI � 9,81 E A E THQRSQOKI E 1000 (12)

Table 10 – Time interval during which hydro pumping stations can pump water to the upper reservoir, [26].

Regarding the generating process, in which water is moved from the upper reservoir to the lower

one, a global efficiency of about 82% was considered. This value is related to the use of equation (13),

40

which is widely used to estimate the power produced by a hydro plant based upon the head and the

water flow rate. This equation is based on equation (10) presented in 3.2.2, but the electrical power is

now expressed in MW.

&'UP*IJKJLMNOKI � 9,81 E A E T E HIJKJLMNOKI1000 � 8 E A E T1000 (13)

It is important to keep in mind that these efficiencies take into account not only the losses in the

turbines and pumps, but also the turbulence and friction losses related with the hydraulic system.

Equations (12) and (13) show the electrical power consumed or produced by the hydro station in MW

because the historical data collected for the year 2007 is all in MW, each value representing the mean

value during a period of two hours.

The technical characteristics of these hydro pumping facilities [25], that are relevant to the

simulations performed in this work, are shown in Table 11. All the hydro plants have their turbines or

pumps with the same rated power, exception made for Vilarinho das Furnas where the installed

turbines have different rated power. As referred in 4.3, this hydro pumping plant does not usually

operate as a pumping facility, thus it has not a limited period of time associated with the pumping

process in opposition to the other facilities listed in Table 10. According to that, in Table 11 there is not

a value for the capacity of the lower reservoir of Vilarinho das Furnas.

Table 11 – Technical characteristics of the pumping hydro stations running in Portugal in 2007.

Hydro Pumping

Power Plants

Upper Reservoir Capacity

[hm3]

Lower Reservoir Capacity

[hm3]

Average Height of the Water Fall [m]

Number of Units Pumps Rated Power [MW]

Turbines Rated Power [MW] Pumps Turbines

Aguieira 216,0 7,85 62,5 3 3 91 112,4

Alqueva 3.150,0 20,89 63,1 2 2 106,9 129,6

Alto Rabagão 550,1 12,45 157,0 2 2 31,7 36,75

Frades 92,1 121,18 46,6 2 2 91,6 91,6

Torrão 22,0 5,96 44,3 2 2 73,3 73

Vilarinho das Furnas 69,7 - 401,4 1 2 78,6 67,7 / 73,6

Table 12 presents the technical minimum power levels at which turbines can work in the hydro

stations, as reported in [26], but there are no minimum limits for the pumps. The reason to this is that

while turbines can operate in a range between its minimum and maximum values by controlling the

intake valve, pumps usually work following an on/off regime with no operating point in between. This

means that the value used to represent the operation of a pumping station is the average power within

41

an interval of two hours, during which the pumps could be working at their rated power only for a

shorter period.

Through equations (12) and (13) and based on the characteristics of Table 11, limitations in the

power of the pumps or the turbines can be translated to limitations in the water flow rate that those

equipments can process. In Table 12, the correspondences between the power limitations of the

equipments and their limitations of water flow rate are shown.

Table 12 – Technical limitations of the equipments on the hydro pumping stations.

Hydro Pumping Power Plants

Pumps Limitations

Turbines Limitations Max.

Turbines Limitations min.

[MW] [m3/s] [MW] [m3/s] [MW] [m3/s]

Aguieira 91,0 103,89 112,4 223,56 73,0 145,20

Alqueva 106,9 120,89 129,6 255,32 55,0 108,36

Alto Rabagão 31,7 14,41 36,75 29,10 20,0 15,84

Frades 91,6 140,26 91,6 244,36 50,0 133,38

Torrão 73,3 118,20 73,0 205,08 40,0 112,37

Vilarinho das Furnas 78,6 13,97 67,7 / 73,6 20,97 / 22,79 35,0 10,84

5.2.2.3. Thermal Plants

In 2007 there were 8 conventional thermal plants working in Portugal and connected to the grid.

The controllability of these power plants together with the negative impact that sudden variations of

the working conditions have on the lifetime and efficiency of the equipments placed these plants as

the most likely suppliers of electrical power in the base of the load diagram.

However, due to the environmental benefits brought up by renewable energies, the conventional

thermal plants often have to reduce their production level in periods with low consumption to allow the

integration of renewable production. To avoid the emergence of stability issues in the system, some

controllable sources of power production (thermal plants, fed by coal or natural gas, or hydro plants

with reservoirs) must always be connected. Thus, the experience gained by operating the Portuguese

electric system showed that, in normal conditions, at least two thermal generating units are always

working, even if at a power level lower than the rated power. In these situations the units that are kept

in operation are one in Sines at a power level of at least 109MW and one in Pego working at least at

101MW. Table 13 shows the technical characteristics of the 8 conventional thermal plants working in

Portugal in the year 2007. The technical limitations of the generating units follow the ones presented in

[26].

42

Table 13 – Technical Characteristics of the Thermal Plants working in 2007, [26].

Thermal Power Plants

Installed Capacity [MW]

Number of Generators

Technical Limits per unit [MW]

Maximum Minimum

Barreiro 56 2 22 15 Carregado 710 6 118,7 / 118,2 36,7 / 36,2

Pego 584 2 292 101 Ribatejo 1176 3 392 235 Setúbal 946 4 236,6 92,2 Sines 1192 4 298 109

Tapada do Outeiro 990 3 330 195 Tunes 197 4 82,5 / 16 4 / 2,5

5.2.3. Hydro Pumping Plants Modelling

In the present work, the hydro power plants, equipped with pumping systems, working in

coordination with wind farms are represented by two reservoirs. Each reservoir is characterized by its

useful capacity in hm3, according to Table 11, and by a variable that indicates the quantity of water

stored in the reservoir.

Among the hydro pumping plants working in 2007 two were selected to operate in coordination

with wind power. If there is a surplus of wind production, relatively to the pre-established value that is

set for the whole year, it is necessary to store that wind production, pumping water from the lower to

the upper reservoir.

The time step in these simulations is two hours, and the value of production for each two hours is

the mean power in that period. Therefore, knowing the average power in a two hours period one can

calculate the water flow rate in m3/s using equation (12), and then multiply it by the number of seconds

in that period (two hours equals 7.200 seconds) to obtain the volume of water that is needed to be

pumped. The same works out when it is necessary to turbine the water to produce energy due to a

lack of wind power production in comparison to the target power value. In this case equation (13) is

used to determine the water flow rate.

Apart from the limitations imposed by the technical characteristics of the equipments to the

operation of the pumping stations, the capacity of the reservoirs is also an important limitation. The

pumping mode of operation is only possible when there is available capacity in the upper reservoir and

while there is water left in the lower reservoir. On the other hand, the generating process is only

possible while there is enough water in the upper reservoir, since it is considered that the lower

reservoirs are not a limitation to this process. When these reservoirs reach their full capacity the

generating process is not stopped; instead, water is released into the river course keeping the

reservoirs full as they receive water from the turbines.

43

According to this, it is important to consider the river inflow into the upper reservoir as it

influences the availability of water in the reservoir, crucial to the generating process, as well as the

available capacity in the reservoir which influences the pumping process. In [27], historical monthly

values for the water flow rate in several rivers are available. The registers include the water flow rates

recorded by monitoring stations installed in the HPPs considered here: Aguieira and Alqueva. Dividing

every monthly value of the water inflow by the number of periods of two hours in each month we

obtain the incoming amount of water into the reservoir in every time step of the simulation. If the

superior reservoirs have not enough capacity to store the incoming water flow, it opens the

dischargers and let the excess water fall to the lower reservoirs maintaining the upper reservoirs full.

The same is applicable to the lower reservoirs, which releases water to the river when its capacity is

reached.

As we consider two hydro pumping plants to coordinate with wind power, the coordination has to

be made not only between wind power and the hydro facilities, but also between both hydro pumping

stations. In this work, the coordination between both pumping hydro plants is made by scheduling to

operate first the hydro plant that has more water stored in the upper reservoir if a generating operation

is needed or in the lower reservoir if pumping is the required operation. The second hydro pumping

plant only operates when the first reaches one of its limitations. For instance, if during a pumping

process the first hydro plant reaches a limitation (reservoir capacity, availability of water...) the second

one is set to operate in order to accommodate the remainder wind production.

In order to cover a set of different scenarios in what concerns the influence of the availability of

water in the upper reservoir, simulations with different initial levels of water in the reservoir are made.

Three different situations were considered: the upper reservoirs are operated at 50%, 75% and 100%

of their maximum capacity.

5.2.4. Wind Parks Modelling

In the present study, wind parks are characterized by its installed capacity. Wind power

production depends basically on wind speed and on the technical characteristics of wind turbines,

such as the power curve. The power curve considered in this work is described by the analytical

expression (6), presented here again, that refers to a wind turbine of 2MW.

&�� '()* �+,-,.0, � 1 4cos � 611 � 7611� � 1, 4 7 � 1 152, 15 7 � 1 250, � 9 25

: (14)

As said before, the variations of wind speed occur in geographical and in temporal bases.

Geographical variations of wind speed are contemplated by choosing different parameters for the

Weibull probability function accordingly to Table 9. This means that in each district wind speed

44

variations over one year follow the same Weibull probability function. In this work 10.000 wind speed

profiles using the Monte-Carlo method were created. Each profile is composed by 4.380 values of

wind speed, corresponding to the periods of two hours in a year. In each profile wind speed follows the

probability function characteristic of that region.

The Weibull parameters that characterize each area in Figure 20 and Figure 21 were determined

for a 60meters height. However, wind turbines with a capacity of 2MW usually have a hub height of

about 80meters. Thus, it is necessary to correct the generated values of wind speed based on the

Weibull parameters to the height of the rotor of the wind turbine. To do so, equation (15), based on the

Prandtl Logarithmic Law already presented in subsection 2.2.2, is used to determine the wind speed

at different heights and taking into account the roughness of ground surface.

�� %� �ln� � "�ln� % "�

(15)

Using equation (14) the wind speed profiles can be converted to wind power production profiles

for a 2MW wind turbine. Multiplying the power profile for this generic wind turbine by the installed

capacity of the corresponding district and dividing it by 2, because it is a 2MW wind turbine, a wind

power production profile for each district is obtained.

The coordination algorithm between wind power and hydro pumping stations is applied to every

one of the 10.000 wind profiles in order to cover a lot of different scenarios of wind and hydro pumping

availability.

5.3. Structure of the Algorithm

In the previous subsections some brief references to the organisation and the structure of the

algorithm developed to coordinate the wind power with two hydro pumping plants were made. In this

section a complete description of the algorithm developed using the software Matlab is carried.

5.3.1. Data presentation

The most important variables that represent the various generating facilities are listed and

described on the following. All of these variables are column vectors with 4.380 elements,

corresponding to a production or consumption profile. Each element of the profile is the mean value of

the power referring to a period of two hours.

- Data from historical records for the year 2007:

45

• VWXYZ[WX\\]\: The power demand recorded in the transmission grid, including the power

flows in the interconnections with the Spanish grid, and the electric losses are grouped in

this variable.

• V^_Z`X: The power output profiles of 21 hydro plants connected to the transmission grid

are considered in this production profile.

• Va]b]cYde]: In this variable are grouped the production profiles of the other renewable

power producers including wind, other hydro, solar photovoltaic, biomass or

cogeneration.

• V^_Z`XVfghibj: In this vector are grouped the production profiles of the hydro pumping

stations that are not being coordinated with wind production (Alto Rabagão, Frades,

Torrão and Vilarinho das Furnas).

- Data created by the algorithm:

• Vkl]`gYe: Production profile for the aggregate of all 8 thermal power plants operating in

Portugal. This profile is created to adjust thermal production to promote the balance

between global generation and load.

• VmibZV`XZfnoiXbpeXdYe : Vector corresponding to the production profile of the global wind power

installed capacity in Portugal.

• Vq\o^VV, VrbZ^VV: Output power profiles of the HPPs assigned to operate in coordination

with wind power.

• sq\o^VV, srbZ^VV: These vectors represent the volume of water that passes though the

turbines or the pumps at every two hours period, according to the output power profiles.

• a]\]`tXi`qq\o^VV, a]\]`tXi`qrbZ^VV: These vectors are the indicators of the volume of

water stored in the upper reservoirs, expressed in m3.

• a]\]`tXi`rq\o^VV, a]\]`tXi`rrbZ^VV: These vectors are the indicators of the volume of

water available in the lower reservoirs, expressed in m3.

• Vujj`]jYo]mibZ[^VV: In this variable is recorded the power profile of the aggregate of wind and both

hydro pumping facilities. According to the strategy adopted in these simulations the

output power level of the aggregate is supposed to be constant during the whole year.

5.3.2. Creating different wind scenarios

The first thing to do is to randomly generate the wind power production profiles for the years 2007

and 2009, using the values for the parameters of Weibull distribution and the installed capacity for

each district – Table 9. In order to obtain a large number of different scenarios of wind power

46

production the Monte-Carlo method was used to generate 10.000 wind profiles based on the installed

capacities per district.

As wind speed variations follow approximately a Weibull probabilistic function, in [28], Wenyuan

Li suggests the implementation of a Monte-Carlo process using the Weibull CDF equal to a random

variable v which follows a uniform distribution, equation (16).

v � �� 1 � �� w� x�y�z (16)

Solving equation (16) in order to determine the wind speed, �, equation (17) is obtained.

� � '� ln�1 � v�*� �⁄ (17)

Based on these two equations the application of the Monte-Carlo method to generate randomly

4.380 values of wind speed constituting a wind speed profile follows two steps:

• Step 1: Generate a uniform distribution random number sequence v between '0, 1*. • Step 2: Calculate the Weibull distribution random variable � using equation (17).

This process is repeated 10.000 times, with the installed capacities of 2007 and 2009, so that

different wind speed profiles for each district are generated allowing the study of coordination between

wind and hydro power in different scenarios.

As previously mentioned, the parameters of Weibull function selected in Table 9 refer to a height

of 60meters; therefore the wind speed values calculated through equation (17) also refer to a

60meters height. Since wind speed significantly changes as the height increases due to the influence

of topography and roughness of the ground’s surface it is important to determine the wind speed at the

height on which the rotor of wind turbines will be placed. However, in order to simplify the modelation

of the wind speed, it was only considered the influence of the roughness of ground’s surface through

equation (15). Considering the Vestas’ V80-2.0MW wind turbine, in [14] a standard hub height is said

to be 80meters. The wind speed profiles for a 60meters height ( %) are transformed in wind speed

profiles for an 80meters height ( �) using equation (15).

The area of interest to study the wind behaviour is the whole national territory which is considered

fragmentally in its 18 districts. The roughness of the ground’s surface changes dramatically between

different districts, and it even changes a lot within the same district. So, as a simplification to the

algorithm, the whole country was considered with the same type of terrain which led to a single value

of the roughness length: " � 0,055� corresponding to a high grass type of terrain Appendix A. Some

other typical values for " are also presented in Appendix A.

47

With the wind speed profiles created it is necessary to determine the corresponding power

profiles. Using the power curve for a generic 2MW wind turbine, equation (14), and the profiles of wind

speed already created, different power production profiles for each district, and for a 2MW wind

turbine, were created. The wind production profiles per district were obtained based on equation (18),

where: &POK|}L~|R�NO~K�O�NLO�N and &%UPPOK|�RL�OKJ are arrays with 4.380 elements representing the power

production of a district and of the generic wind turbine, respectively; &�K�NM��J|�MQM�ON��O�NLO�N is an array with 18

elements representing the installed capacity of wind power in each district.

&POK|}L~|R�NO~K�O�NLO�N '()* � &%UPPOK|�RL�OKJ E &�K�NM��J|�MQM�ON��O�NLO�N E 12 (18)

In order to obtain a unique and global wind production profile (&POK|}L~|R�NO~K��~�M� � referring to the

whole Portuguese territory the profiles for the different districts are added according to equation (19).

&POK|}L~|R�NO~K��~�M� � � &POK|}L~|R�NO~K�O�NLO�N ��K��K��

(19)

5.3.3. Wind-Hydro Coordinated Operation

The coordination between wind and hydro power aims to maintain constant the output power

production of the aggregate. The first step is to select the hydro plants to work in a complementary

regime to wind power. The level of power that is wanted to be continuously supplied by the aggregate

(&�IILJIMNJNMLIJN ) is set taking in consideration the installed capacity of the hydro pumping plants, because

when the wind speed is lower than the cut-in speed of the wind turbines there would not be wind

power supplied to the electric system. In these situations the hydro pumping plants must be able to

supply &�IILJIMNJNMLIJN , the total output power set for the aggregate.

Using a single hydro plant in coordination with all wind power could only guarantee a set point

corresponding to an amount of power equal or lower to the installed capacity of the turbines. More

than one hydro plant is needed to achieve a set point of the output power at a significant level. In this

work two hydro pumping plants that maximize both the generating and pumping capacity were

selected: Aguieira and Alqueva. These two hydro plants totalize an installed capacity of 596,4MW for

the turbines and 486,8MW for the pumps, according to Table 11.

The target value for the output power of the aggregate that it is supposed to supply continuously

must then be lower than 596,4MW to assure that even in periods with no wind power, the hydro plants

are able to supply the amount of power specified. Furthermore, by using two hydro plants instead of

just one we are also increasing the storage capacity of water in both reservoirs.

The historical data for the year 2007 regarding the buses of the transmission grid described in

section 5.2.1 refer to the renewable energy production sources in Portugal; therefore it contains the

48

wind power production recorded in that year. Since in this work wind production profiles are created

independently from the historical data records it is necessary to subtract from the global renewable

production the energy generated by wind.

Considering the simulations based on the wind installed capacity of the year 2007 it is necessary

to discount the wind energy production from that year, which was 4.007GWh – Table 9. Dividing the

wind production by the number of hours in the year (8.760 hours) the mean value per hour of the

power that was generated by wind (457,42 MW) is obtained. This value is subtracted in every two

hours average values of the renewable energy production profile. Obviously this assumes that wind

production in that year was constant during the whole year which was not true, due to the variability

characteristic of wind speed. For the simulations based on the wind capacity of 2009, the value to be

subtracted in the production profile of the renewable energy producers is 849,32MW which was

determined dividing the wind production of 2009 (7.440GWh) by the number of hours in a year.

Once the sources of energy production and their production profiles are identified, it is now

possible to start with the coordination algorithm. The following procedure is repeated 4.380 times, for

every period of two hours, so the whole year is covered. However there is a difference between the

first period of two hours and the next periods. In the first period the initial values for the level of water

in the reservoirs of the hydro plants must be set, whereas in the following periods there is no need to

specify the initial values. It is important to highlight that in every period of two hours the first thing to do

is to update the levels of storage in the upper reservoirs, by adding to the already stored volume of

water the inflow from the river course.

The strategy for coordinating both HPPs with wind power production is based on the principle that

the hydro plant which has the higher volume of water stored in the upper reservoir is the first to be

considered to be dispatched for generating, while the one that has the higher volume in the lower

reservoir is the first to be dispatched for pumping. This means that one hydro plant has priority over

the other, instead of both having equal priorities. According to that, the primary HPP adjusts its

operating plan according to wind production and to the target value of production for the aggregate. If

it is not able to supply or consume the necessary amount of power, the secondary HPP is assigned to

satisfy the previously specified output power of the aggregate.

5.3.3.1. Pumping mode of operation

Comparing the global wind power production value, &POK|}L~|R�NO~K��~�M� , with the target power,

&�IILJIMNJNMLIJN , the operation plan for the primary HPP, which is the one with the largest amount of water

stored in the lower reservoir, follows equation (20).

&��N�}} � &�IILJIMNJNMLIJN � &POK|}L~|R�NO~K��~�M� (20)

49

If &��N�}} is a negative value, it means that the hydro pumping facility has to consume that amount

of power pumping water to the upper reservoir. The first limitation to this type of operation is the rated

power of the pumps: if the absolute value of &��N�}} is higher than the sum of the rated power of all

pumps in the hydro station, it will not be possible to pump the desired volume of water, but only the

share of that volume that corresponds to the rated power of the pumps.

It is now necessary to determine the volume of water that corresponds to that amount of power in

order to check if is possible to pump it to the upper reservoir. Manipulating equation (12) the volume of

water to be pumped is calculated, multiplying the volume flow rate, A'�B �⁄ *, by the number of

seconds in a period of two hours (7200 seconds), as shown in equation (21).

A��N�}}'S�* � &��N�}}'UP* E HQRSQOKI E 1000 E 72009,81 E T (21)

Regarding the restriction to the operation of the hydro station caused by the limited capacity in

the upper reservoir, it only becomes an issue when the volume to be pumped, A��N�}}'S�* , added to the

one already stored in the reservoir surpasses the capacity of the basin. In such a case, the amount of

water that is pumped must decrease to equal the difference between the total capacity of the reservoir

and the actual quantity of water in it. On the other hand, if the upper reservoir has enough available

capacity to accommodate the desired volume of water, full pumping may be carried.

Among the several limitations to the pumping process considered in this work, the availability of

water in the lower reservoir was also addressed. The volume of water to be pumped must also

decrease if there is not enough water available. If we subtract the updated A��N�}}'S�* from the volume of

water stored in the lower reservoir and it results in a negative value, it means that there is not enough

water to pump. In this case the HPP will pump up all the water left in the lower reservoir emptying it.

After this, the level indicators of both reservoirs are updated according to the volume of water set

to be moved up. The power consumed by the hydro plant is determined, after the influence of all

technical limitations, by equation (22) solved to calculate &��N�}} when A��N�}} is known. In these

calculations, the head T is kept constant at the levels of Table 11.

&��N�}}'UP* � A��N�}}'S�* E 9,81 E THQRSQOKI E 1000 E 7200 (22)

Once defined the operation point of the primary HPP and considering its limitations of installed

capacity and storage in the reservoirs, one must check if it is necessary to dispatch the secondary

HPP. Using equation (23) the power output for the secondary hydro plant is determined (remember

that &��N�}} is a negative value when the hydro plant is working as a pumping station, and that only

occurs when wind production exceeds the target power value).

50

&%K|�}} � &�IILJIMNJNMLIJN � &POK|}L~|R�NO~K��~�M� � &��N�}} (23)

If &%K|�}} equals zero, it means that the primary hydro plant is able to accommodate all wind

production. On the other hand, a negative value for &%K|�}} indicates the power level at which the

secondary hydro plant must operate while pumping. All the restrictions to its operation must be

checked to define the new operation point as it was done to the primary hydro plant.

The power consumed by both hydro pumping plants may not be enough to accommodate the

surplus of wind production. In these cases the aggregate of wind and hydro power does not supply the

target power, but a superior value, which indicates that more pumping capacity or storage capacity is

needed.

5.3.3.2. Generating mode of operation

In what concerns to the structure of the algorithm, the differences between the operation of the

hydro plant as a pumping station or as a generating facility are not many.

The HPPs are assigned to operate in the generating mode in periods when there is a lack of wind

and consequently wind power cannot supply by itself the targeted power, &�IILJIMNJNMLIJN . Equation (20) is

used to determine the output power that the hydro pumping station must provide to compensate the

low production of wind power. However, due to technical limitations of the turbines they may not be

able to supply &��N�}}. Other restrictions might come from the availability of water in the upper

reservoir. If there is not enough water it will not be possible to generate the desired power,

nevertheless the available water in the reservoir is used to generate the corresponding power, which

can be determined through equation (24).

&��N�}}'UP* � A��N�}}'S�* E 9,81 E T E HIJKJLMNOKI1000 E 7200 (24)

At this point a new problem might arises, related with the minimum power level at which the hydro

turbines can operate. If the value of &��N�}} from equation (24) is lower than the technical minimum of

the turbines, presented in Table 12, none of the turbines will work; therefore the output power of the

hydro plant will be zero.

When the power production from the primary HPP is not enough to maintain the output power of

the aggregate, the secondary one is called up to supply the remaining amount of power needed to

compensate the lack of wind production, which is determined by equation (23). Since the HPPs are

operating as generators their output power &��N�}} and &%K|�}} is positive, therefore equation (23) is

still valid.

51

The operation of the secondary HPP is limited by its own constraints, so it might be incapable of

supplying the amount of power determined by equation (23), but only a lower value. If that value is

even lower than the technical minimum of the turbines this hydro plant could not operate at all or it

could operate at its minimum level if the primary hydro plant could reduce its production to a level still

higher than its own technical minimum. The second option is preferable since it might allow the

aggregate to supply the target power while the first option does not. If it is not possible to reduce the

production in the primary hydro plant, the secondary one will not operate.

Once the operating points of both HPPs are defined, their power output and the volumes of water

to be moved are known. It is then necessary to update the indicators of the level of water in every

reservoir. The lower reservoirs are not a constraint when the hydro plant is operating as a generating

facility and has to drop water from the upper basin. If the quantity of water to be dropped is larger than

the empty capacity of the lower reservoir, it will be filled up and the surplus of water is released to the

water course.

5.3.3.3. Matching power production with demand

As wind production profiles are created randomly, hydro pumping stations and thermal power

plants, due to their controllability, have to adjust their production to promote the correspondence

between load and generation in the electric system. Equation (25) shows the adjustment to be made

by thermal generation according to the operating points defined previously for both hydro plants in

coordination with wind power.

&��JLSM� � &�~M|[�~��J� � &��|L~ � &�JKJ�M��J � &��|L~}RSQOKI � &POK|}L~|R�NO~K��~�M� � &��N�}} � &%K|�}} (25)

However, thermal power plants also have technical limitations to their operation, as shown in

Table 13. Therefore, the next step is to verify if the value obtained for the thermal power production

from equation (25) is lower than the minimum limit in which thermal production in Portugal can work, in

order to guarantee the stability of the electric system. Experience obtained in the operation of the

electric system allowed setting the minimum value of thermal production to a value of 210MW, which

corresponds to the operation of one generator unit in Sines and one in Pego, both working at their

technical minimum (109MW and 101MW, as shown in Table 13). However, in this work the value for

the minimum of thermal production was set in 205,22MW that was the value recorded in the historical

data. The difference between the theoretical value and the practical one is justified by the power

consumption that both power plants have to support their auxiliary services, which is about 5 MW.

If the value that results from equation (25) is lower than 205,22MW it is necessary to increase it to

that value. As a result of the increase in thermal production, and because it is mandatory to keep the

balance between generation and load, it is also necessary to adjust the output power of other

controllable power producers, such as the hydro plants assigned to the coordination with wind

production. However, by changing the previously established value for the output power of the hydro

52

plants the continuous supply of the targeted value of production for the aggregate is automatically

compromised.

The adjustments to be made on the output power of the hydro plants depend on several factors:

the amount of power that was increased in thermal generation, the current operation point of the hydro

plants or the volumes of water stored in the reservoirs. Five distinct situations are possible at this

point; all of them are analysed on the following.

5.3.3.3.1. One HPP as a generator

When one of the hydro plants is working as a generator and the other is stopped, the strategy

adopted was to first decrease the production of the working hydro plant, which may lead to a value

that is lower than the technical minimum of the turbines. In this case the hydro plant is stopped and, to

compensate that, thermal power plants increase their production.

If reducing the hydro power production is not enough, it is necessary to increase the power

consumption by setting the hydro plants to pump up water. The first hydro plant to start pumping is the

one that has the higher volume of water available in the lower reservoir. If the first hydro plant cannot

consume the necessary amount of power to compensate the increase in thermal production, then the

second hydro plant is assigned to pump water too to increase the load as much as needed. Due to the

referred restrictions in the pumping process hydro plants might not be able to increase the load

enough and therefore the balance between load and generation is not achieved.

5.3.3.3.2. Both HPPs as generators

When both hydro plants are operating as generators to compensate the low value of wind

production, it was opted to primarily decrease the production of the HPP that has the lower volume of

water stored in the upper reservoir. If the new output power of that hydro plant is lower than the

technical minimum of its turbines the hydro plant is stopped and thermal generators increase their

level of production to guarantee the balance between load and generation. On the other hand, if it is

not enough to decrease the production in one of the hydro plants, the other HPP also decreases its

output power level while the first one is already stopped.

Shutting down both hydro plants might also be insufficient to compensate the augment of thermal

production. Therefore it could be required to reverse the operation of the hydro plants, setting them to

pump up water. In that case, the first hydro plant to start pumping is the one with more water stored in

the lower reservoir. In case of impossibility to consume the necessary amount of power by this hydro

plant, due to its restrictions, the other is also set to run as a pumping station, consuming the remaining

power. Due to the limitations in the operation of the hydro plants they might be incapable of

consuming all the needed power and consequently the balance between load and generation is

compromised.

53

5.3.3.3.3. Both HPPs stopped

When both hydro plants were stopped, either due to their restrictions or because wind power

equals &�IILJIMNJNMLIJN , the solution to balance load and generation was to increase the power consumption

by setting to pump up water the HPP with the largest amount of water stored in the lower reservoir. If

the operation of this hydro plant is not enough to increase the load as it is needed, the other hydro

plant must also operate as a pumping station.

The balance between global power demand and generation is achieved if the HPPs successfully

pump up the volume of water correspondent to the amount of power increased in thermal production.

The technical limits of the pumps as well as constraints in the reservoirs may lead to the incapacity of

the hydro plants to increase the load as much as needed.

5.3.3.3.4. One HPP pumping

When only one of the hydro plants is pumping, it is due to the fact that that hydro plant is capable

of accommodate the surplus of wind production on its own, or to the fact that the other hydro plant was

supposed to be pumping as well but it is not due to some technical constraints.

The strategy adopted here is to increase the consumption of the already pumping hydro plant. If

that is not enough to compensate the increase in thermal production, the other hydro plant is assigned

to the pumping process too. Constraints to the pumping process may result in an unbalance between

the global generation and load of the electric system.

5.3.3.3.5. Both HPPs pumping

When the wind production level is much higher than the target value for the output power of the

aggregate, both hydro plants may be assigned to work as pumping stations in order to accommodate

that surplus of wind production. However, the necessity to increase the level of thermal production to

its technical minimum results in an obligatory increase of the power consumed by the hydro plants on

their pumping process.

The only hydro plant capable of increasing its power consumption level is the one that has the

lower quantity of water available in the lower reservoir, because that hydro plant was only assigned to

the pumping operation because the other had already reached one of its technical constraints. If the

second HPP cannot satisfy the mandatory increase of the system’s load the balance between

generation and consumption is not possible.

5.3.3.3.6. Closing Remarks

Through these points the restrictions for the operation of the hydro plants were repeatedly

mentioned. Their importance lies on the setting of the possible operation points for the hydro plants.

After the definition of the output power values for each hydro plant as well as the volumes of water to

54

be moved between reservoirs, the indicators of the levels of water in every reservoir are updated to

supply an updated background to the simulation of the next time period.

Whenever the balance between load and generation was compromised, due to the referred

constraints on the operation of the HPPs, different solutions were available to promote that balance:

the curtailment of some wind production or the use of the interconnections with the Spanish grid to

drain the excess of production. However, none of these options was used in this study since its goal is

to accommodate internally all the wind power production in Portugal, by coordinating it with two HPPs.

In those unbalanced situations no measures were taken in this work to promote that balance but they

were useful to highlight the necessity of more pumping or more storage capacity in the HPPs.

55

6. Results

In this chapter are described the simulations performed in this work as well as presented and

analyzed the results obtained.

6.1. Performed Simulations

With the joint operation of all wind power and the two selected hydro plants (Aguieira and

Alqueva) it is wanted a continuous supply, during a whole year, of a certain amount of power.

Since this study was done using both hydro pumping plants mentioned above, the total installed

capacity for the turbines and for the pumping systems is 596,4MW and 486,8MW, in that order. For

that reason the first set of simulations done was to a target power value (&�IILJIMNJNMLIJN ) equal to 500MW.

This value was chosen to be lower than the installed capacity of the turbines of both hydro stations

because they must be able to supply the &�IILJIMNJNMLIJN in periods when wind power is low or absent.

It was also studied the possibility of supplying continuously a target power equal to 750MW with

the same aggregate of wind and hydro power facilities.

The target power value was defined taking in consideration the profile of the power demand seen

by the transmission grid (including the losses and power flows on the interconnections). The lower

value recorded in 2007 for the power demand was around 2.300MW. Thus, target powers of 500MW

or 750MW to be continuously supplied by the aggregate are adequate values, as they represent

approximately a fifth and a third of the lower value of power demand recorded. Obviously, in periods of

higher demand the aggregate would lose weight on the production mix.

For each target power several simulations were performed in order to understand the influence of

the different characteristics of hydropower stations in their performance when coordinating with wind

power. Moreover, to study the influence of the installed capacity of wind power, the simulations were

run using at first the wind capacity of the year 2007 (2.446MW – Table 1) and then the capacity of

2009 (3.566MW – Table 1). In order to cover different scenarios of wind power production, all

simulations were repeated 10.000 times using the different wind power profiles created for both

installed capacities and considering the Weibull parameters for the Portuguese territory (Table 9).

The figures presented subsequently show the number of simulations in which it was possible to

maintain the output power of the aggregate equal to the target value for a certain percentage of the

year. In each figure the results are shown for different simulations that are identified by a number (for

example “sim0” or “sim4”). The conditions on which those simulations were run were the following:

56

• sim0: real values of the installed capacity of turbines and pumping systems as well as of

the storage capacity of the reservoirs;

• sim1 to sim4: the installed capacity of the pumping systems is increased repeatedly

from two times to five times the real capacity, while the other characteristics are kept in

the real values;

• sim5: the storage capacity of the lower reservoirs is doubled, while the other

characteristics of the hydro stations are kept in the real value;

• sim6 to sim9: the installed capacity of the pumping systems is increased repeatedly

from two times to five times the real capacity, while the storage capacity of the lower

reservoirs is doubled;

• sim10: the installed capacity of the turbines is doubled, while the other characteristics

are kept in the real values;

• sim11: the storage capacity of the upper reservoirs is doubled, while the other

characteristics of the hydro stations are kept in the real values;

• sim12: both the installed capacity of the turbines and the storage capacity of the upper

reservoirs are doubled, while the other characteristics are kept in the real values;

• sim13: the installed capacity of the turbines and pumping systems, the storage capacity

of the upper and lower reservoirs are increased until the aggregate of wind power and

both HPPs successfully supplies the target power for at least 80% of the year and for all

the 10.000 different wind profiles.

The goal of this coordinated operation was to guarantee that the aggregate was capable of

supplying continuously the target power during the whole year. However, after the first simulations,

that goal revealed to be impossible due to the technical limitations of the equipments. Therefore, a

more modest goal was set: the joint operation of all the wind power and both HPPs must supply to the

electric system the target power for at least 80% of the year, for all the different 10.000 wind profiles,

as referred in sim13.

6.2. Results for different values of the Aggregate Target Power

On the following will be presented some of the results obtained from the simulations performed in

this study using the algorithm described in chapter 5. In order to summarize the reading and the

analysis of the results only the most important results are presented here. However, in the Appendix B

all the results that support the following figures are detached.

6.2.1. Wind Installed Capacity of the year 2007: 2.446MW

6.2.1.1. Aggregate Target Power: 500MW

For the target power of 500MW were run the simulations from

subsection are presented only the results for

In order to understand the relevance of the amount of water stored in the upper reservoirs of the

hydro dams for maintaining the output power of the aggregate at 500MW, all the simulations were

made in three different scenarios: first, considering both upper reservoirs at the beginning of the year

at their full capacity; second, considering the reservoirs with an initial level of water equal to 75% of

their storage capacity; third, considering th

occupied. The inferior reservoirs of the hydropower plants were always considered full in the

beginning of the simulations since it improves the pumping process providing a higher availability of

water to be pumped and it does not influences the generating process.

In Figure 22, Figure 23 and

superior reservoirs, the number of times, in view of the 10.000 different wind scenarios, in which it was

possible to the aggregate to supply 500MW during the percentages of the year in the horizontal axis.

Figure 22 – Results for a target power of 500MW

reservoirs initially at 100% of their storage capacity.

0

2000

4000

6000

8000

10000

10% 20%

Nu

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Percentage of the year with P

Ptarget=500MW, upper reservoir initially at 100% capacity

57

Aggregate Target Power: 500MW

For the target power of 500MW were run the simulations from sim0 to sim9

re presented only the results for sim0, sim4, sim5 and sim9.


the output power of the aggregate at 500MW, all the simulations were



their storage capacity; third, considering the reservoirs initially with 50% of their storage capacity

The inferior reservoirs of the hydropower plants were always considered full in the


ter to be pumped and it does not influences the generating process.

and Figure 24 are shown, for diverse initial levels of storage in the

of times, in view of the 10.000 different wind scenarios, in which it was


Results for a target power of 500MW and a wind capacity of 2.446MW, when considering the upper


30% 40% 50% 60% 70% 80%

Percentage of the year with Paggregate = Ptarget

=500MW, upper reservoir initially at 100% capacity

sim9, although in this


the output power of the aggregate at 500MW, all the simulations were



e reservoirs initially with 50% of their storage capacity

The inferior reservoirs of the hydropower plants were always considered full in the


are shown, for diverse initial levels of storage in the

of times, in view of the 10.000 different wind scenarios, in which it was


when considering the upper

80% 90%


sim0

sim4

sim5

sim9


reserv




All the simulations listed before (from

equal to 750MW. In this situation

the HPPs to allow the aggregate to supply the t

In Figure 25 are presented the results for the target power of 750MW and for the superior

reservoirs initially at 100% of th

conditions: the installed capacity of the turbines was twice the real value; the storage capacity of the

upper reservoirs was raised to five times the real value.

0

2000

4000

6000

8000

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10% 20%

Nu

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Ptarget=500MW, upper reservoir inittially at 75% capacity

0

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58





Power: 750MW

All the simulations listed before (from sim0 to sim13) were run for the aggregate target power

equal to 750MW. In this situation the objective was to analyse what would be the changes needed in

s to allow the aggregate to supply the target value for at least 80% of the year.

are presented the results for the target power of 750MW and for the superior

reservoirs initially at 100% of their capacity. In this situation, sim13 was run on the following


upper reservoirs was raised to five times the real value.

30% 40% 50% 60% 70% 80%


=500MW, upper reservoir inittially at 75% capacity

30% 40% 50% 60% 70% 80%





) were run for the aggregate target power

to analyse what would be the changes needed in

arget value for at least 80% of the year.

are presented the results for the target power of 750MW and for the superior

was run on the following


80% 90%


sim0

sim4

sim5

sim9

80% 90%


sim0

sim4

sim5

sim9



The results for the simulations with the reservoirs initially at 75% of the storage capacity are

presented in Figure 26. The conditions of

the real value; the storage capacity of the upper reservoirs was raised to six times the real value.



With the superior reservoirs initially at half capacity, the results obtained are presented in

27. In this case, sim13 was run with the installed capacity of the turbines twice the real value and the

storage capacity of the upper reservoirs raised to eight times the real value.

0

2000

4000

6000

8000

10000

10% 20%

Nu

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0

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59




. The conditions of sim13 were: the installed capacity of the turbines was twice


Results for a target power of 750MW and a wind capacity of 2.446MW, when consideri


With the superior reservoirs initially at half capacity, the results obtained are presented in

was run with the installed capacity of the turbines twice the real value and the

storage capacity of the upper reservoirs raised to eight times the real value.

30% 40% 50% 60% 70% 80%



30% 40% 50% 60% 70% 80%





pacity of the turbines was twice



With the superior reservoirs initially at half capacity, the results obtained are presented in Figure

was run with the installed capacity of the turbines twice the real value and the

80% 90%


sim0

sim4

sim5

sim9

sim10

sim11

sim13

90%


sim0

sim4

sim5

sim9

sim10

sim11

sim13

Figure 27 – Results for a target power


6.2.2. Wind Installed Capacity of the year 2009: 3


In order to compare with the results obtain

simulations using the wind capacity of 2009

also run sim13 to understand in what conditions it would be possible to achieve the goal of 80%

coverage of the year at the target power.

simulations sim0, sim4, sim5, sim9 and sim13 with the aggregate target power equal to 500MW, for

different initial levels of the upper reservoirs: 100%, 75% and 50%,

The results presented for simulation sim13

turbines raised to five times the real value, the storag

reservoirs were raised to 20 times and 200 times the real values, in that order.

0

2000

4000

6000

8000

10000

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Nu

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60



Wind Installed Capacity of the year 2009: 3.566MW


In order to compare with the results obtained in 6.2.1.1 for the wind capacity

using the wind capacity of 2009 were the same: sim0 – sim9. However, at this point we

sim13 to understand in what conditions it would be possible to achieve the goal of 80%

coverage of the year at the target power. Figure 28, Figure 29 and Figure 30 show the results for


different initial levels of the upper reservoirs: 100%, 75% and 50%, in that order.

for simulation sim13 in Figure 28 were obtained with the capacity of the

turbines raised to five times the real value, the storage capacities of the superior and inferior

reservoirs were raised to 20 times and 200 times the real values, in that order.

30% 40% 50% 60% 70% 80%




for the wind capacity of 2007 the

sim9. However, at this point we

sim13 to understand in what conditions it would be possible to achieve the goal of 80%

show the results for the


were obtained with the capacity of the

e capacities of the superior and inferior

90%


sim0

sim4

sim5

sim9

sim10

sim11

sim13

Figure 28 – Results for a target power of

reservoirs initially at

With the superior reservoirs starting the year at 75% of their capacity the results of

were obtained. In these conditions,

times the real value, the storage capacities of the superior and inferior reservoirs were raised to 40

times and 200 times the real values, i

Figure 29 – Results for a target power of


The results for sim13 of Figure


times and 200 times the real values, in that order.

0

2000

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6000

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10000

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Nu

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0

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Ptarget=500MW, upper reservoir inittially at 75% capacity

61



With the superior reservoirs starting the year at 75% of their capacity the results of

. In these conditions, sim13 was done with the capacity of the turbines raised to five





Figure 30 were obtained with the capacity of the turbines raised to five



30% 40% 50% 60% 70% 80%



30% 40% 50% 60% 70% 80%




With the superior reservoirs starting the year at 75% of their capacity the results of Figure 29

was done with the capacity of the turbines raised to five



were obtained with the capacity of the turbines raised to five


80% 90%


sim0

sim4

sim5

sim9

sim13

90%


sim0

sim4

sim5

sim9

sim13

Figure 30 – Results for a target power of 50


6.2.2.2. Aggregate Target Power: 75

Setting the target power of the aggregate at 750MW, the simulations run

capacity of 2009 (3.566MW) provided the results presented in the following figures. To allow the

comparison between these results and those obtained in

same. In Figure 31 the initial levels of the superior reservoirs is set to 100% of the storage capacity,

while in Figure 32 it is 75% and in

For the different initial levels of the superior reservoirs of the HPPs,

same conditions: the storage capacity of t

values.



0

2000

4000

6000

8000

10000

10% 20%

Nu

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0

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62




Setting the target power of the aggregate at 750MW, the simulations run

566MW) provided the results presented in the following figures. To allow the

comparison between these results and those obtained in 6.2.1.2 the simulations performed were the

the initial levels of the superior reservoirs is set to 100% of the storage capacity,

it is 75% and in Figure 33 the initial level is 50%.

For the different initial levels of the superior reservoirs of the HPPs, sim13 was run always in the

same conditions: the storage capacity of the upper reservoirs was raised to three times the real



30% 40% 50% 60% 70% 80%



30% 40% 50% 60% 70% 80%




Setting the target power of the aggregate at 750MW, the simulations run with the wind power

566MW) provided the results presented in the following figures. To allow the

the simulations performed were the

the initial levels of the superior reservoirs is set to 100% of the storage capacity,

was run always in the

he upper reservoirs was raised to three times the real


90%


sim0

sim4

sim5

sim9

sim13

80% 90%


sim0

sim4

sim5

sim9

sim10

sim11

sim13





6.3. Discussion of the Results

At first will be discussed and analysed the results obtained with the target

500MW and then the results for 750MW.

the wind capacity of 2007 and of 2009 are compared.

6.3.1. Aggregate Target Power: 500MW

6.3.1.1. Wind Installed Capacity

0

2000

4000

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63





the Results

At first will be discussed and analysed the results obtained with the target power value equal to

500MW and then the results for 750MW. For each value of the target power the results obtained with

the wind capacity of 2007 and of 2009 are compared.


Wind Installed Capacity: 2.446MW

30% 40% 50% 60% 70% 80%



30% 40% 50% 60% 70% 80%





power value equal to

For each value of the target power the results obtained with

80% 90%


sim0

sim4

sim5

sim9

sim10

sim11

sim13

80% 90%


sim0

sim4

sim5

sim9

sim10

sim11

sim13

64

According to Figure 22 and Figure 23, the results obtained using the real characteristics of the

hydropower stations (sim0) are already satisfactory since the aggregate is capable of maintaining the

target power value during at least 80% of the year, for almost all the 10.000 wind profiles. However it

cannot reach 90% of the year in these conditions. Analysing Figure 24 for sim0, one can see that

decreasing the initial level of storage in the reservoirs to 50% will affect the fulfilment of 80% of the

year at the target power.

In the simulations sim1 to sim4, the increase of the pumping capacity of the HPPs was translated

in an increase of the performance of the system, since it was capable of supplying the target power

during 90% of the year for most of the 10.000 wind profiles. Only increasing it to three times the real

pumping capacity it was possible to guarantee the coverage of 90% of the year for the majority of the

wind scenarios as it can be verified in the Appendix B.1.

Analysing Figure 22, Figure 23 and Figure 24, the comparison of sim0 and sim4 with sim5 and

sim9, in that same order, in which the capacity of the inferior reservoirs is doubled, allow us to

conclude that the capacity of the inferior reservoirs is not a constraint for the operation of the

coordinated system, for this wind installed capacity and this target power.

A finest analysis of the results show that starting the year with 75% of storage in the upper

reservoirs, instead of 100%, improves the results slightly for the simulations with higher pumping

installed capacities (sim3 and sim4). This can be explained by the more frequent availability of empty

volume in the upper reservoirs allowing the hydro stations to pump up more water.

The worst results obtained for the simulations with the reservoirs initially at 50% of their capacity

are explained by the unavailability of water in those reservoirs when it is needed to generate

electricity.

6.3.1.2. Wind Installed Capacity: 3.566MW

Raising the installed capacity of wind power from 2.446MW to 3.566MW means an increase of

1.120MW. Since the wind capacity of 2009 is much higher than the target power output of the

aggregate, there are more periods during the year requiring the pumping process to accommodate the

surplus of wind power. Therefore a higher storage capacity of the hydro dams to achieve the goal of

80% of the year at the target power level is needed.

Comparing the situations with the superior reservoirs at 100% of their capacity in the beginning of

the year (Figure 22 and Figure 28), one can see that with the wind capacity of 2007 it was possible to

achieve the goal of 80% for all the 10.000 different wind scenarios just by doubling the pumping

installed capacity; with the wind capacity of 2009 one could only assure the supplying of 500MW

during 30% of the year for every 10.000 wind profiles. Even in the conditions of sim13 (the pumping

capacity was raised to five times the real value; the storage capacity of the lower reservoirs is raised

to 200 times the real value and the upper ones to 20 times) that are unrealistic and impossible to

obtain, we could only guarantee 30% for all wind profiles and 40% for some of them.

65

This incapacity of maintaining the output power of the aggregate equal to the target power,

fulfilling the goal of 80% of the year, is related with the high level of wind installed capacity in 2009. As

the wind capacity increased from 2.446MW (in 2007) to 3.566MW (in 2009) the HPPs are more often

requested to pump and in those situations the amount of water to be pumped also increases. Since

the HPPs did not have the necessary pumping and storage capacities, as the wind capacity increased

the results obtained dropped for the target power of 500MW.

As the initial level of the superior reservoirs decreases to 75% (Figure 29) and 50% (Figure 30),

the results slightly improve, increasing to almost 10.000 the number of wind profiles in which 40% of

the year is guaranteed at the target power. The goal of 80% of the year was only achieved in sim13

when the pumping capacity was raised to five times the real value, the capacity of the lower reservoirs

was raised to 200 times the real value and the capacity of the upper ones to 40 times, if the reservoirs

started the year at 75% of their capacity, and to 20 times, if they started at 50%. Anyway, these

conditions are unrealistic, particularly the increase in the capacity of the reservoirs due to the large

areas of flooding that it would require.

6.3.2. Aggregate Target Power: 750MW


When the target power was 750MW, the results obtained in the simulations with the real

characteristics of the hydro stations (sim0) are not satisfactory. As shown in Figure 25 the best

situation is the coverage of 30% of the year, but only for around 1.000 simulations, when starting with

the upper reservoirs full. If the initial value of the storage in the upper reservoirs is set to 75% (Figure

26) or to 50% (Figure 27) the aggregate could never reach 30% of the year.

Comparing the simulations sim0, sim4, sim5 and sim9, one can see that the increase of the

pumping capacity as well as the increase of the storage capacity of the inferior reservoirs has no

positive effect on the performance of the system. This suggests that it was not the pumping process

that was impelling those adverse results, but they might be due to constraints in the generating

process.

Since the real installed capacity of the turbine-generator units (596,4MW) is lower than the

aggregate target value (750MW), in periods with no wind or low wind the hydro plants are not capable

of supplying the remaining power. Therefore, in sim10 was increased the installed capacity for twice

the real value (1.192,8MW). In this simulation the results slightly improved when starting with the

reservoirs at full capacity, but still only 30% of the year was guaranteed at the target power.

In sim11 the capacity of the superior reservoirs is doubled and the results improve in relation with

the ones obtained for sim0. When starting with the reservoirs at 100% of their capacity it was possible

to guarantee always 30% of the year at the target power and 40% of the year for more than half of the

10.000 wind profiles. The results are worst when the reservoirs started at 75% or 50% of their

66

capacity, suggesting that the capacity of the upper reservoir is the major constraint to the fulfilment of

the 80% goal.

The installed capacity of the turbines in sim13 (1.192,8MW) was already higher than the target

value avoiding the restrictions observed in sim10. In Figure 25 one can see that the aggregate is

capable of supplying the target power for at least 80% of the year, and even 90%, for all wind profiles

when the upper reservoirs started at their full capacity. However, to do so it was necessary to increase

the storage capacity of the upper reservoirs to five times the real capacity.

When the reservoirs began at 75% of their capacity, Figure 26, it was also covered 80% of the

year at all times and 90% in almost a third of the simulations. The storage capacity of the upper

reservoirs had to be raised to six times the real capacity.

The worst case for sim13 is verified when the reservoirs initially were at 50% of their capacity,

Figure 27, because to cover 80% of the year it was necessary to raise the storage capacity of superior

reservoirs to eight times their real capacity.

These results suggest that increasing the target value for the output power of the aggregate make

the generating process a major constraint. In order to fulfil the pre-established goal of covering at least

80% of the year at the target value, it would be necessary to increase the installed capacity of the

turbines to a value higher than the target power of the aggregate and to increase the storage capacity

of the upper reservoirs. While the upgrade of the turbines may be viable, increasing the storage

capacity by five, six or eight times is not an option due to the environmental effects associated with the

flooding of that area. It is important to remind that both hydro dams used in this study (Aguieira and

Alqueva) are among the ones with the highest storage capacity.


While the results for the target power of 500MW get worst when raising the wind capacity from

2.446MW to 3.566MW, when the target power was 750MW the results improved significantly. With the

wind capacity of the year 2007 the results were around 30% - 40% of the year, whereas with the wind

capacity of 2009 it was possible to guarantee 70% of the year for all wind profiles in most of the

simulations, independently of the initial level of the upper reservoirs (Figure 31, Figure 32 and Figure

33), which is close to the established goal of 80%.

In sim0, for the reservoirs initially at full capacity (Figure 31), it was achieved 80% of the year for

111 wind profiles, while just by increasing the pumping capacity to twice the real value the aggregate

could supply the target power during 80% for 9.967 wind profiles among the 10.000 different

scenarios.

Raising the storage capacity of the superior reservoirs to twice the real capacity (sim11) one can

assure the 80% coverage of the year for almost all wind profiles, especially when the initial level of the

superior reservoirs is 100% and 75% (Figure 31 and Figure 32). For an initial level of 50% in the upper

reservoirs, 80% of the year was achieved for almost half of the different wind scenarios (Figure 33).

67

Independently of the initial levels of the superior reservoirs in sim13, the goal of 80% of the year

with the output power of the aggregate equal to 750MW could always be accomplished just by

increasing the storage capacity of the upper reservoirs to three times the real values.

Comparing the results of sim13 for the cases with the wind capacity of 2007 and 2009 one can

conclude that in the second case it was not necessary to raise the installed capacity of the turbines to

a value higher than 750MW. This can be explained by the fact that with the increase of wind capacity

to 3.566MW the number of periods in which wind power is lower than 750MW is reduced,

consequently it will not be necessary to increase the capacity of the turbines.

68

7. Conclusions

In this last chapter are exposed the conclusions of this study regarding the feasibility of the

coordination between wind and hydro power aiming to firm the output power of this aggregate. It is

also suggested some future work that can be done in this subject.

7.1. Final Considerations

This thesis allowed to highlight the possibilities of using the coordination between wind and hydro

power facilities with the aim of firming their output power production.

The results achieved by the coordination algorithm depended widely on the target power level set

to be continuously supplied and on the wind installed capacity. For the wind capacity of 2007

(2.446MW) and using the real characteristics of the hydro facilities (sim0), a target value of 500MW

could be satisfied during 80% of the year for almost all the wind profiles tested. However, when the

target power was raised to 750MW, the results dropped to around 30% of the year.

For that same simulation (sim0) and with the wind capacity of 2009 (3.566MW), better results

were obtained for the target power of 750MW, in which it was possible to satisfy that target power for

around 80% of the year, while for a target power of 500MW the results were around 30% or 40%.

Based on these results, one can conclude that as the wind installed capacity increases, the target

value to be supplied continuously by the mix of wind and hydro power should be readjusted to keep

the aim of 80% of the year at the target power a possible goal. With the real characteristics of the

HPPs used in this study (sim0), the goal of 80% was almost always achieved when the target power

was around a fifth of the wind installed capacity (target power equal to 500MW with the wind capacity

equal to 2.446MW or target power equal to 750MW with a wind capacity of 3.566MW). Although, for

higher values of wind installed capacity, even adjusting the target power, it would be necessary to

upgrade the pumping and generating capacity as well as to increase the storage capacity of the

reservoirs.

The definition of the proper target power level to be satisfied by the aggregate of wind and hydro

power is not a simple task. For higher values of wind installed capacity, the range of variation of the

power production between windy periods and periods with no wind is also higher. Therefore, if the

target value is low compared with the wind installed capacity the pumping process is prevalent over

the generating process, and so a high pumping capacity is required as well as a high storage capacity

in the lower and in the upper reservoirs, which is similar to sim13, for the wind capacity equal to

3.566MW and the target power equal to 500MW.

On the other hand, if the target power is closer to the wind installed capacity, the generating

process gains relevance due to the number of periods in which the wind production is lower than the

target value. This situation would require a high installed capacity of the turbine-generator units and a

69

high storage capacity in the superior reservoirs, which was the solution adopted in the simulation

sim13 for the wind capacity equal to 2.446MW and the target power equal to 750MW.

Based on the results obtained in this study, one can conclude that the coordination between wind

and hydro pumping stations with the goal of maintaining constant the power production of their

aggregate is only technically viable in some conditions. The target power to be continuously injected in

the grid cannot be very high or the technical characteristics of the hydro plants must be unrealistically

upgraded. In this study was defined a goal of at least 80% of the year at the target power, which was

hardly achieved. If a more ambitious goal is pretended, for instance 90%, the necessary upgrades to

be made in the hydro facilities would be even more severe and insupportable.

It is important to keep in mind that a goal of 100% is impossible to achieve due to the technical

minimum levels of the turbines. When the wind power production is slightly lower than the target

power the HPPs are assigned to generate a small amount of power which may implicate that the

turbines should operate at a level lower than their technical minimum. In these situations the turbines

do not operate at all and target power is not supplied.

This study suggests that in a smaller scale the coordinated operation could be feasible and

profitable. If one considers a local wind park and a small hydro plant, with a great height between both

reservoirs and a significant storage capacity, the coordination between them may result in the supply

of a firmed target power during almost 100% of the year. In these cases, as the target power is lower

than the ones used in this study, the turbines used in the HPP must have lower technical minimums.

A limitation of this study while considering the firming of all the wind power production of Portugal

was that it did not consider the power flows in the transmission grid. As the wind parks are spread

over a large area of the Portuguese territory, their power production must be transported to the HPPs

for their pumping operation. The power lines may not have enough capacity available to transport that

electricity, a fact that was not contemplated in this study. This fact reinforces the possibility of the

coordination in a local area, where the wind parks would be near the hydro plants and the bottlenecks

in the transmission grid would not be an issue.

7.2. Future work

This study was made based on the principle of an isolated electric system, in which the global

demand and losses must be supplied by the inner generating facilities connected to the system.

However, most electric systems, including the Portuguese, are not isolated but are connected to other

neighbour systems instead. Some work can be done in this area, considering the possibility of using

the interconnections in the transmission grid to drain the surplus of wind production if the system

operator is not capable of matching generation with demand by adjusting other generating facilities or

by storing wind production, avoiding the curtailment of a renewable source production.

Further studies can also focus on the power flows in the Portuguese grid necessary to the

pumping process and on the capacity of the power lines to transmission that electricity.

70

As the results suggested, the capacity of storage needed in the hydropower dams is exaggerated

when the wind power installed capacity increases. A form of obviating this issue is using HPPs with

higher heads (hundreds of meters), because it reduces the volumes of water to be transferred

between reservoirs for the same amount of power. Some studies can also be done using these types

of hydro facilities.

Instead of attempting to firm the wind production of the global wind power capacity, a similar

study can be carried out but in a smaller level. A possibility could be to firm the wind production in a

regional or local level coordinating a wind park with a small HPP. This could be interesting for the

owners of the wind and hydro facilities since it would allow them to guarantee to the operator of the

electric system a continuous supply of a certain amount of power using renewable energy sources.

As an alternative for a fixed value of the target power to be supplied, in MW, this target power

could be a fixed percentage of the power demand. This would result in higher levels of production in

peak periods and lower levels of production in off-peak periods.

Another interesting study to be done in this subject is to evaluate the economical feasibility of the

coordinated operation, using knowledge of pricing electricity from wind power in the electricity

markets. The coordination would only be profitable if the price paid during the pumping process is

lower than the one at which the electricity is sold when injected in the grid.

71

References

[1]. United Nations Framework Convention on Climate Change. [Online] http://unfccc.int.

[2]. MEID - Ministério da Economia, da Inovação e do Desenvolvimento. ENE2020 - Estratégia

Nacional para a Energia. [Online] 2010. http://www.min-economia.pt/.

[3]. MEID - Ministério da Economia, da Inovação e do Desenvolvimento. Energias Renováveis em

Portugal. [Online] Julho de 2007. http://www.min-economia.pt/.

[4]. Resolução do Conselho de Ministros n.º 29/2010.

[5]. EWEA - The European Wind Energy Association. Wind in power - 2009 European statistics.

February 2010.

[6]. REN - Redes Energéticas Nacionais. Dados Técnicos Electricidade - Valores Provisórios. 2009.

[7]. WWEA - World Wind Energy Association. World Wind Energy Report. 2009.

[8]. Rodrigues, Álvaro. Parques Eólicos em Portugal. s.l. : Instituto de Engenharia Mecânica e Gestão

Industrial, INEGI, 2008.

[9]. DGEG - Direcção Geral de Energia e Geologia. Renováveis, Estatisticas Rápidas

Novembro/Dezembro 2009.

[10]. Estanqueiro, Ana e Costa, Paulo. Energia Eólica Offshore - Levantamento do potencial do país,

limitações e soluções tecnológicas. s.l. : LNEG - Laboratório Nacional de Energia e Geologia.

[11]. Castro, Rui M. G. Introdução à Energia Eólica. s.l. : Folhas de Energias Renováveis e Produção

Descentralizada, Março 2008.

[12]. Wind Atlases of the World. [Online] www.windatlas.dk.

[13]. INETI - Instituto Nacional de Engenharia, Tecnologia e Inovação. Potencial Eólico em Portugal

Continental.

[14]. Danish Wind Industry Association. [Online] www.windpower.org.

[15]. Vestas. V80-2.0MW brochure. [Online] www.vestas.com.

[16]. IHA - International Hydropower Association. Activity Report 2010.

[17]. IEA - International Energy Agency. Key World Energy Statistics. 2009.

[18]. Programa Nacional de Barragens com Elevado Potencial Hidroeléctrico - Memória. Novembro

2007.

[19]. INAG - Instituto da Água I.P. PNBEPH - Programa Nacional de Barragens de Elevado Potencial

Hidroeléctrico. [Online] http://pnbeph.inag.pt.

72

[20]. REN - Redes Energéticas Nacionas. Potencial Hidroeléctrico Nacional, Importância Sócio-

Económica e Ambiental do seu Desenvolvimento. Novembro 2006.

[21]. Paiva, José Pedro Sucena. Redes de Energia Eléctrica - Uma Análise Sistémica. Lisboa : IST Press,

2005.

[22]. Wind-Hydro Integration: Pumped Storage to Support Wind. Montero, Fernando Perán e Pérez,

Juan J. s.l. : Hydroworld, Hydro Review, June 2009.

[23]. Wind Energy Storages - Possibilities. Spahic, Ervin, et al. s.l. : IEEE, 2007.

[24]. Energy storage options for improving wind power quality. Lund, P. D. e Paatero, J. V. Espoo,

Finland : Helsinki University of Technology, 2006.

[25]. EDP - Energias de Portugal. [Online] http://www.a-nossa-energia.edp.pt/centros_produtores/.

[26]. Faias, Sérgio Miguel Redondo. Balancing Electricity Generation and Demand with Increasing

Integration of Renewable Energy: An Application to the Portuguese Power System. s.l. : Instituto

Superior Técnico / Instituto Superior de Engenharia de Lisboa, (to be published).

[27]. SNIRH - Sistema Nacional de Informação de Recursos Hídricos. [Online] www.snirh.pt.

[28]. Li, Wenyuan. Risk Assessment of Power Systems. s.l. : Wiley Interscience - IEEE Press, 2005.

73

Appendix A

In Table 14 are presented some usual values of z0 corresponding to different types of roughness

of the ground’s surface.

Table 14 – Typical values of the roughness length z0, [11].

Type of Terrain z0 min [m] z0 Max [m]

Mud / ice 10�� 3 E 10�� Flat sea 2 E 10�� 3 E 10��

Sand 2 E 10�� 10�B Snow 10�B 6 E 10�B

Cereals field 10�B 10�% Short grass 10�% 4 E 10�% Open field 2 E 10�% 3 E 10�%

High grass 4 E 10�% 10��

Land with trees 10�� 3 E 10��

Forest 10�� 1

Village of the suburbs 1 2

City centre 1 4

74

Appendix B

In this Appendix B are presented all the values that resulted from the simulations performed in

this study and that support the figures presented in chapter 6.

B.1 – Results for a wind capacity of 2.446MW and a target power of 500MW

Table 15 – Results obtained with the upper reservoirs initially at 100% of their capacity, for 2.446MW of wind

capacity and 500MW of target power.

Percentage of the year covered at the target power

10% 20% 30% 40% 50% 60% 70% 80% 90%

Real characteristics of the HPPs

sim0 10000 10000 10000 10000 10000 10000 10000 9940 0

2X, 3X, 4X and 5X the pumping capacity

sim1 10000 10000 10000 10000 10000 10000 10000 10000 263

sim2 10000 10000 10000 10000 10000 10000 10000 10000 7915

sim3 10000 10000 10000 10000 10000 10000 10000 10000 8898

sim4 10000 10000 10000 10000 10000 10000 10000 10000 8954

2X the storage capacity of the lower reservoirs

sim5 10000 10000 10000 10000 10000 10000 10000 9947 0

2X, 3X, 4X and 5X the pumping capacity and 2X the storage capacity of the lower reservoirs

sim6 10000 10000 10000 10000 10000 10000 10000 10000 276

sim7 10000 10000 10000 10000 10000 10000 10000 10000 8124

sim8 10000 10000 10000 10000 10000 10000 10000 10000 9028

sim9 10000 10000 10000 10000 10000 10000 10000 10000 9096




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 10000 10000 10000 10000 9024 0


sim1 10000 10000 10000 10000 10000 10000 10000 10000 393

sim2 10000 10000 10000 10000 10000 10000 10000 10000 8273

sim3 10000 10000 10000 10000 10000 10000 10000 10000 9087

sim4 10000 10000 10000 10000 10000 10000 10000 10000 9137


75

sim5 10000 10000 10000 10000 10000 10000 10000 9047 0


sim6 10000 10000 10000 10000 10000 10000 10000 10000 415

sim7 10000 10000 10000 10000 10000 10000 10000 10000 8462

sim8 10000 10000 10000 10000 10000 10000 10000 10000 9193

sim9 10000 10000 10000 10000 10000 10000 10000 10000 9250




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 10000 10000 10000 10000 30 0


sim1 10000 10000 10000 10000 10000 10000 10000 9999 0

sim2 10000 10000 10000 10000 10000 10000 10000 10000 54

sim3 10000 10000 10000 10000 10000 10000 10000 10000 97

sim4 10000 10000 10000 10000 10000 10000 10000 10000 102


sim5 10000 10000 10000 10000 10000 10000 10000 36 0


sim6 10000 10000 10000 10000 10000 10000 10000 9999 0

sim7 10000 10000 10000 10000 10000 10000 10000 10000 69

sim8 10000 10000 10000 10000 10000 10000 10000 10000 112

sim9 10000 10000 10000 10000 10000 10000 10000 10000 119

76





10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 1064 0 0 0 0 0 0


sim1 10000 10000 973 0 0 0 0 0 0

sim2 10000 10000 884 0 0 0 0 0 0

sim3 10000 10000 881 0 0 0 0 0 0

sim4 10000 10000 881 0 0 0 0 0 0


sim5 10000 10000 1064 0 0 0 0 0 0


sim6 10000 10000 975 0 0 0 0 0 0

sim7 10000 10000 884 0 0 0 0 0 0

sim8 10000 10000 881 0 0 0 0 0 0

sim9 10000 10000 881 0 0 0 0 0 0

2X the turbines capacity

sim10 10000 10000 7182 0 0 0 0 0 0

2X the storage capacity of the upper reservoirs

sim11 10000 10000 10000 5793 0 0 0 0 0

2X the turbines capacity and 2X the storage capacity of the upper reservoirs

sim12 10000 10000 10000 10000 0 0 0 0 0


sim13 10000 10000 10000 10000 10000 10000 10000 10000 10000




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 0 0 0 0 0 0 0


sim1 10000 10000 0 0 0 0 0 0 0

sim2 10000 10000 0 0 0 0 0 0 0

sim3 10000 10000 0 0 0 0 0 0 0

77

sim4 10000 10000 0 0 0 0 0 0 0


sim5 10000 10000 0 0 0 0 0 0 0


sim6 10000 10000 0 0 0 0 0 0 0

sim7 10000 10000 0 0 0 0 0 0 0

sim8 10000 10000 0 0 0 0 0 0 0

sim9 10000 10000 0 0 0 0 0 0 0


sim10 10000 10000 0 0 0 0 0 0 0


sim11 10000 10000 10000 0 0 0 0 0 0


sim12 10000 10000 10000 744 0 0 0 0 0


sim13 10000 10000 10000 10000 10000 10000 10000 10000 2929




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 9957 0 0 0 0 0 0 0


sim1 10000 9960 0 0 0 0 0 0 0

sim2 10000 9958 0 0 0 0 0 0 0

sim3 10000 9959 0 0 0 0 0 0 0

sim4 10000 9959 0 0 0 0 0 0 0


sim5 10000 9957 0 0 0 0 0 0 0


sim6 10000 9960 0 0 0 0 0 0 0

sim7 10000 9958 0 0 0 0 0 0 0

sim8 10000 9959 0 0 0 0 0 0 0

sim9 10000 9959 0 0 0 0 0 0 0


sim10 10000 10000 0 0 0 0 0 0 0


sim11 10000 10000 1094 0 0 0 0 0 0


sim12 10000 10000 9993 0 0 0 0 0 0

78


sim13 10000 10000 10000 10000 10000 10000 10000 10000 0

79





10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 45 0 0 0 0 0


sim1 10000 10000 10000 1380 0 0 0 0 0

sim2 10000 10000 10000 2300 0 0 0 0 0

sim3 10000 10000 10000 2562 0 0 0 0 0

sim4 10000 10000 10000 2613 0 0 0 0 0


sim5 10000 10000 10000 45 0 0 0 0 0


sim6 10000 10000 10000 1376 0 0 0 0 0

sim7 10000 10000 10000 2299 0 0 0 0 0

sim8 10000 10000 10000 2559 0 0 0 0 0

sim9 10000 10000 10000 2609 0 0 0 0 0

5X the pumping capacity, 20X the storage capacity of the upper reservoirs and 200X the storage capacity of the upper reservoirs

sim13 10000 10000 10000 2609 0 0 0 0 0




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 3941 0 0 0 0 0


sim1 10000 10000 10000 8671 0 0 0 0 0

sim2 10000 10000 10000 9328 0 0 0 0 0

sim3 10000 10000 10000 9458 0 0 0 0 0

sim4 10000 10000 10000 9471 0 0 0 0 0


sim5 10000 10000 10000 4481 0 0 0 0 0


sim6 10000 10000 10000 8981 0 0 0 0 0

sim7 10000 10000 10000 9514 0 0 0 0 0

80

sim8 10000 10000 10000 9612 0 0 0 0 0

sim9 10000 10000 10000 9629 0 0 0 0 0


sim13 10000 10000 10000 10000 10000 10000 10000 10000 19




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 7887 0 0 0 0 0


sim1 10000 10000 10000 9791 0 0 0 0 0

sim2 10000 10000 10000 9933 0 0 0 0 0

sim3 10000 10000 10000 9950 0 0 0 0 0

sim4 10000 10000 10000 9949 0 0 0 0 0


sim5 10000 10000 10000 8417 0 0 0 0 0


sim6 10000 10000 10000 9880 0 0 0 0 0

sim7 10000 10000 10000 9959 0 0 0 0 0

sim8 10000 10000 10000 9975 0 0 0 0 0

sim9 10000 10000 10000 9975 0 0 0 0 0


sim13 10000 10000 10000 10000 10000 10000 10000 10000 19

81





10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 10000 10000 10000 10000 111 0


sim1 10000 10000 10000 10000 10000 10000 10000 9967 0

sim2 10000 10000 10000 10000 10000 10000 10000 9476 0

sim3 10000 10000 10000 10000 10000 10000 10000 8537 0

sim4 10000 10000 10000 10000 10000 10000 10000 8229 0


sim5 10000 10000 10000 10000 10000 10000 10000 215 0


sim6 10000 10000 10000 10000 10000 10000 10000 9970 0

sim7 10000 10000 10000 10000 10000 10000 10000 9078 0

sim8 10000 10000 10000 10000 10000 10000 10000 7171 0

sim9 10000 10000 10000 10000 10000 10000 10000 6516 0


sim10 10000 10000 10000 10000 10000 10000 6 0 0


sim11 10000 10000 10000 10000 10000 10000 10000 9997 0


sim12 10000 10000 10000 10000 10000 10000 10000 0 0


sim13 10000 10000 10000 10000 10000 10000 10000 10000 0




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 10000 10000 10000 9894 0 0


sim1 10000 10000 10000 10000 10000 10000 10000 6811 0

sim2 10000 10000 10000 10000 10000 10000 10000 6319 0

sim3 10000 10000 10000 10000 10000 10000 10000 5733 0

82

sim4 10000 10000 10000 10000 10000 10000 10000 5621 0


sim5 10000 10000 10000 10000 10000 10000 9921 0 0


sim6 10000 10000 10000 10000 10000 10000 10000 7007 0

sim7 10000 10000 10000 10000 10000 10000 10000 6010 0

sim8 10000 10000 10000 10000 10000 10000 10000 5074 0

sim9 10000 10000 10000 10000 10000 10000 10000 4789 0


sim10 10000 10000 10000 10000 10000 10000 0 0 0


sim11 10000 10000 10000 10000 10000 10000 10000 9999 0


sim12 10000 10000 10000 10000 10000 10000 10000 0 0


sim13 10000 10000 10000 10000 10000 10000 10000 10000 0




10% 20% 30% 40% 50% 60% 70% 80% 90%


sim0 10000 10000 10000 10000 10000 10000 151 0 0


sim1 10000 10000 10000 10000 10000 10000 10000 114 0

sim2 10000 10000 10000 10000 10000 10000 10000 134 0

sim3 10000 10000 10000 10000 10000 10000 10000 97 0

sim4 10000 10000 10000 10000 10000 10000 10000 93 0


sim5 10000 10000 10000 10000 10000 10000 207 0 0


sim6 10000 10000 10000 10000 10000 10000 10000 150 0

sim7 10000 10000 10000 10000 10000 10000 10000 108 0

sim8 10000 10000 10000 10000 10000 10000 10000 63 0

sim9 10000 10000 10000 10000 10000 10000 10000 56 0


sim10 10000 10000 10000 10000 10000 10000 0 0 0


sim11 10000 10000 10000 10000 10000 10000 10000 4651 0


sim12 10000 10000 10000 10000 10000 10000 10000 0 0

83


sim13 10000 10000 10000 10000 10000 10000 10000 10000 0

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